Abrégé

The present disclosure discloses a method for predicting the battery performance based on a combination of material parameters of a battery pulping process, including obtaining a target prediction model; and obtaining a combination of material parameters to be predicted corresponding to the battery pulping process, and inputting the combination of the material parameters to be predicted into the target prediction model to obtain a target battery performance level corresponding to the combination of the material parameters to be predicted. The method of the present disclosure adopts a mathematical model method instead of manual testing, can quickly predict battery performance levels corresponding to different combinations of material parameters, and solves the problem that in the prior art, it is necessary to conduct separate tests for different input ratios of various materials to determine the impact of different material ratios on the battery performance.

Classes IPC  ?

• G01R 31/367 - Logiciels à cet effet, p.ex. pour le test des batteries en utilisant une modélisation ou des tables de correspondance
• G06N 3/045 - Combinaisons de réseaux
• G06N 3/0985 - Optimisation d’hyperparamètres; Meta-apprentissage; Apprendre à apprendre

Abrégé

Provided is the use of two-dimensional nanomaterials in the inhibition of a coronavirus, and specifically disclosed is the use of the two-dimensional nanomaterials in the preparation of a medicament for treating or preventing diseases caused by a coronavirus or of a material for adhering to or inhibiting the coronavirus. The two-dimensional nanomaterial is selected from the group consisting of copper indium thiophosphate (CIPS) nanosheet, graphene oxide nanosheet, molybdenum disulfide nanosheet, black phosphorus nanosheet and mixtures thereof. The coronavirus is selected from one of HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1, SARS-CoV, SARS-CoV2 or MERS-CoV. The diseases caused by the coronavirus are diseases caused by coronavirus infection. The material has the advantages of being simple to prepare, having a high biological safety and an excellent effect.

Classes IPC  ?

• A61K 9/70 - Bases pour bande, feuille ou filament
• A01N 25/34 - Formes façonnées, p.ex. feuilles, non prévues dans l'un quelconque des autres sous-groupes du présent groupe principal
• A01N 59/00 - Biocides, produits repoussant ou attirant les animaux nuisibles, ou régulateurs de croissance des végétaux, contenant des éléments ou des composés inorganiques
• A01N 59/16 - Métaux lourds; Leurs composés
• A01N 59/26 - Phosphore; Ses composés
• A01P 1/00 - Désinfectants; Composés antimicrobiens ou leurs mélanges
• A61K 33/24 - Métaux lourds; Leurs composés
• A61K 33/42 - Phosphore; Ses composés
• A61K 33/44 - Carbone élémentaire, p.ex. charbon de bois, noir de carbone
• A61K 45/06 - Mélanges d'ingrédients actifs sans caractérisation chimique, p.ex. composés antiphlogistiques et pour le cœur 
• A61P 31/14 - Antiviraux pour le traitement des virus ARN
• B82Y 5/00 - Nanobiotechnologie ou nanomédecine, p.ex. génie protéique ou administration de médicaments

Abrégé

An image data quality evaluation method and apparatus, a terminal device, and a readable storage medium. The image data quality evaluation method includes: inputting three-dimensional image data to be evaluated into a feature extraction network model for processing to obtain a feature matrix; processing the feature matrix on the basis of a plurality, of branch network models in a hypemetwork model to obtain a plurality of parameter matrixes, and respectively adjusting, on the basis of the plurality of parameter matrixes, parameters of a plurality of fully connected layers in a corresponding regression model; and processing the feature matrix on the basis of the adjusted regression model to obtain a quality evaluation score. The dynamic adjustment of parameters of a model is implemented on the basis of content of input data, so that the processing efficiency and the quality evaluation precision for three-dimensional image data are improved.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06T 15/00 - Rendu d'images tridimensionnelles [3D]
• G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées

Abrégé

The invention relates to a method for constructing an obligate anaerobic Salmonella strain, the obligate anaerobic Salmonella strain constructed by using said method, and the use thereof in tumor therapy.

Classes IPC  ?

• A61K 35/74 - Bactéries
• A61K 45/06 - Mélanges d'ingrédients actifs sans caractérisation chimique, p.ex. composés antiphlogistiques et pour le cœur 
• C12N 1/20 - Bactéries; Leurs milieux de culture
• A61P 35/00 - Agents anticancéreux
• C12N 1/38 - Stimulation chimique de la croissance ou de l'activité par addition de composés chimiques qui ne sont pas des facteurs essentiels de croissance; Stimulation de la croissance par élimination d'un composé chimique

Abrégé

A low-dose PET image restoration method and system, a device, and a medium are provided. The method includes: S1, performing blocking processing on a training image comprising a low-dose PET image, an MR image, and a standard-dose PET image to obtain a first patch, and performing first preprocessing on the first patch to obtain a second patch; S2, obtaining, according to the second patch, a first joint dictionary by means of sparse coding and dictionary updating; and S3, restoring the low-dose PET image to a restored image of the standard-dose PET image according to the first joint dictionary.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p.ex. de visages similaires sur les réseaux sociaux

Abrégé

The present application provides an image-driven brain atlas construction method and apparatus, a device and a storage medium, and involves in the field of medical imaging technologies. The method includes: acquiring a node feature matrix, where the node feature matrix includes time sequences of multiple nodes of a brain; performing hypergraph data structure transformation on the node feature matrix to acquire a first hypergraph incidence matrix; inputting the first hypergraph incidence matrix and the node feature matrix into a trained hypergraph transition matrix generator for processing to output and acquire a first hypergraph transition matrix, where the first hypergraph transition matrix characterizes a constructed multi-modal brain atlas. The technical solution provided by the present application can construct the multi-modal brain atlas, and this multi-modal brain connection structure can express more feature information. When it is applied to the brain disease diagnosis process, the accuracy of disease diagnosis can be improved.

Classes IPC  ?

• G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux
• G06T 7/00 - Analyse d'image

Abrégé

Disclosed are a process parasitism-based branch prediction method and device for serverless computing, an electronic device, and a readable storage medium. The method includes: receiving a calling request of a user for a target function; when capacity expansion is required, scheduling a container executing the target function to a new server that has not executed the target function in a preset period of time, wherein a parasitic process is pre-added to a base image of the container; triggering the parasitic process when the container is initialized on the new server, the parasitic process being used for initiating a system call, and triggering a system kernel to select a target template function according to the type of the target function and copying the target template function N times; using execution data of the copied N target template functions as training data to train a branch predictor on the new server.

Classes IPC  ?

• G06F 9/38 - Exécution simultanée d'instructions
• G06N 5/046 - Inférence en avant; Systèmes de production

Abrégé

Provided are a biomedical tape, a preparation method thereof and use thereof. The biomedical tape comprises a hydrogel carrier in dry state and a functional nanomaterial encapsulated within the hydrogel carrier in dry state, and the hydrogel carrier in dry state comprises a thin film body of hyaluronic acid hydrogel and a dopamine-modified polyacrylic acid permeated into a surface of the thin film body of hyaluronic acid hydrogel. The preparation method for the biomedical tape comprises: preparing a hyaluronic acid hydrogel with the functional nanomaterial dispersed therein, and drying and curing the hydrogel to form a film to obtain the thin film body of hyaluronic acid hydrogel; and preparing a dopamine-modified polyacrylic acid solution, and permeating the solution into a surface of the thin film body of hyaluronic acid hydrogel by coating to obtain the biomedical tape.

Classes IPC  ?

• A61L 24/08 - Polysaccharides
• A61L 24/02 - Adhésifs ou ciments chirurgicaux; Adhésifs pour dispositifs de colostomie contenant des matériaux inorganiques
• A61L 24/00 - Adhésifs ou ciments chirurgicaux; Adhésifs pour dispositifs de colostomie
• A61L 24/06 - Adhésifs ou ciments chirurgicaux; Adhésifs pour dispositifs de colostomie contenant des matériaux macromoléculaires obtenus par des réactions faisant intervenir uniquement des liaisons carbone-carbone non saturées
• A61L 24/10 - Polypeptides; Protéines

Abrégé

The present disclosure relates to the field of image processing technologies, and provides an ultrasound image segmentation method and apparatus, a terminal device, and a storage medium. With the method, simulated ultrasound images are synthesized based on Computed Tomography (CT) images. An image segmentation model is pre-trained using the synthesized simulated ultrasound images. The pre-trained image segmentation model is migrated, by employing a transfer learning method, to real sample ultrasound images for further training to obtain a final image segmentation model. A segmentation processing on an ultrasound image to be segmented is completed by the final image segmentation model. In this way, the ultrasound images synthesized based on the CT images can be used to replace a part of training data, thereby solving a problem of lack of training data when training the image segmentation model.

Classes IPC  ?

• G06T 7/149 - Découpage; Détection de bords impliquant des modèles déformables, p.ex. des modèles de contours actifs

Abrégé

The present disclosure relates to the technical field of image processing and provides a motion estimation method and apparatus for a tumor, a terminal device, and a storage medium. The method includes: obtaining a current value of a respiratory correlation signal of a patient, the respiratory correlation signal reflecting a motion trajectory feature of a designated organ with the tumor of the patient in each of different respiratory states; inputting the current value of the respiratory correlation signal into a tumor motion estimation model to obtain an estimated current position of the tumor; and inputting the estimated current position of the tumor into an organ motion estimation model to obtain an estimated current velocity vector field of the designated organ. By adopting the motion estimation method, it realizes a respiratory motion estimation for the whole organ and enhance accuracy of positioning the tumor and vital anatomical structures around the tumor.

Classes IPC  ?

• G16H 50/50 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour la simulation ou la modélisation des troubles médicaux
• G06T 7/73 - Détermination de la position ou de l'orientation des objets ou des caméras utilisant des procédés basés sur les caractéristiques
• G06T 7/246 - Analyse du mouvement utilisant des procédés basés sur les caractéristiques, p.ex. le suivi des coins ou des segments
• G06T 7/00 - Analyse d'image

Abrégé

A method for determining a protein structure using cryo-electron microscopy, including: enabling a target protein to contain a tag; enabling a resulting target containing the tag to bind a scaffold protein to form a complex between the target protein and the scaffold protein; and performing single-particle imaging using the cryo-electron microscopy to determine a structure of the target protein in complex with the scaffold protein. The scaffold protein is any one of streptavidin, avidin, or derivatives thereof. The tag is configured for selectively binding to the scaffold protein. The tag is one selected from the group consisting of: a biotin tag, comprising a biotin; a biotinylated protein or polypeptide tag, comprising a protein sequence and a biotin covalently linked to the protein sequence; a Strep-tag; and a biotinylated or strep-tagged antibody, or antibody Fab fragment, or single-chain antibody.

Classes IPC  ?

• G01N 23/2251 - Recherche ou analyse des matériaux par l'utilisation de rayonnement [ondes ou particules], p.ex. rayons X ou neutrons, non couvertes par les groupes , ou en mesurant l'émission secondaire de matériaux en utilisant des microsondes électroniques ou ioniques en utilisant des faisceaux d’électrons incidents, p.ex. la microscopie électronique à balayage [SEM]
• G01N 23/2202 - Préparation d’échantillons à cet effet

Abrégé

The present application is applicable to the field of medical imaging technologies, and provides an image-driven brain atlas construction method and apparatus, a device and a storage medium. The method includes: acquiring multi-modal data of a brain to be predicted, where the multi-modal data is acquired according to image data collected when the brain is under at least three different modalities; inputting the multi-modal data into a preset fusion network for processing to output and acquire feature parameters of the brain; where the processing of the multi-modal data by the fusion network includes: extracting a non-Euclidean spacial feature and an Euclidean spacial feature of the multi-modal data, and performing hypergraph fusion on the non-Euclidean spacial feature and the Euclidean spacial feature to acquire the feature parameters, where the feature parameters are used to characterize a brain connection matrix and/or a disease category of the brain.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux

Abrégé

A method and a device for a three-dimensional reconstruction of brain structure, and terminal equipment. The method includes steps of: obtaining a 2D image of a brain, inputting the 2D image of the brain into a 3D brain point-cloud reconstruction model that has been trained to be processed, and outputting a 3D point-cloud of the brain. The 3D brain point-cloud reconstruction model includes a ResNet encoder and a graphic convolutional neural network. The ResNet encoder is configured to extract a coding feature vector of the 2D image of the brain, and the graphic convolutional neural network is configured to construct the 3D point-cloud of the brain according to the coding feature vector.

Classes IPC  ?

• G06T 9/00 - Codage d'image
• G06T 19/20 - Transformation de modèles ou d'images tridimensionnels [3D] pour infographie Édition d'images tridimensionnelles [3D], p.ex. modification de formes ou de couleurs, alignement d'objets ou positionnements de parties
• G06T 17/00 - Modélisation tridimensionnelle [3D] pour infographie

Abrégé

Provided are an orthopedic repair scaffold, a preparation method thereof and use thereof. The orthopedic repair scaffold is a three-dimensional porous scaffold. A material of the orthopedic repair scaffold comprises the following components in mass percentage: 80%-95% of a biodegradable polymer and 5%-20% of a biodegradable nanoparticle, where the biodegradable nanoparticle is a nanoparticle of manganese compound. The preparation method of the orthopedic repair scaffold comprises: preparing a homogeneous solution comprising a biodegradable polymer and a biodegradable nanoparticle according to the mass percentage; preparing the homogeneous solution through a curing molding process into a molded three-dimensional porous scaffold; and freeze-drying the molded three-dimensional porous scaffold to obtain the orthopedic repair scaffold. The orthopedic repair scaffold can better promote healing of a bone injury and has an excellent mechanical performance and a good medical imaging function.

Classes IPC  ?

• A61L 27/44 - Matériaux composites, c. à d. en couches ou contenant un matériau dispersé dans une matrice constituée d'un matériau analogue ou différent comportant une matrice macromoléculaire
• A61L 27/58 - Matériaux au moins partiellement résorbables par le corps
• A61L 27/56 - Matériaux poreux ou cellulaires
• A61L 27/02 - Matériaux inorganiques
• A61F 2/30 - Articulations

Abrégé

The present invention discloses a real-time ultrasonic stimulation electric signal recording chip and a preparation method thereof, where the preparation method includes the following steps: S1 manufacturing an interdigital electrode on a piezoelectric substrate to obtain a surface acoustic wave chip, and manufacturing a recording electrode and an electrode lead; S2, manufacturing an insulation protection layer on the chip obtained in the S1, and processing the insulation protection layer to form the recording electrode, so as to obtain a chip combining the interdigital electrode and the recording electrode; S3, preparing a PDMS cavity; and S4, bonding the PDMS cavity prepared in the S3 and the chip obtained in the S2. In the present invention, combining the interdigital electrode generating a surface acoustic wave ultrasound with a multi-channel recording electrode, such that real-time recording of a multi-channel electric signal under ultrasonic stimulation is achieved.

Classes IPC  ?

• G01N 29/02 - Analyse de fluides
• H03H 9/25 - Réseaux comprenant des éléments électromécaniques ou électro-acoustiques; Résonateurs électromécaniques - Détails de réalisation de résonateurs utilisant des ondes acoustiques de surface
• H03H 9/02 - Réseaux comprenant des éléments électromécaniques ou électro-acoustiques; Résonateurs électromécaniques - Détails
• H03H 3/10 - Appareils ou procédés spécialement adaptés à la fabrication de réseaux d'impédance, de circuits résonnants, de résonateurs pour la fabrication de résonateurs ou de réseaux électromécaniques pour la fabrication de résonateurs ou de réseaux utilisant des ondes acoustiques de surface pour obtenir une fréquence ou un coefficient de température désiré

Abrégé

The present application provides an ultrasonic wake-up system. The system includes an ultrasonic imaging device, an ultrasound stimulation device, and an ultrasound stimulation effect evaluation device, and acquires an ultrasonic image of a target object through the ultrasonic imaging device, transmits an ultrasound to the target object based on the ultrasonic image through the ultrasound stimulation device, and adjusts the transmitted ultrasound required through the ultrasound stimulation effect evaluation device. Therefore, peripheral nerves are accurately stimulated, an uplink reticular wake-up system is activated, so as to wake up patients with disorders of consciousness.

Classes IPC  ?

• A61N 7/00 - Thérapie par ultrasons
• A61B 8/00 - Diagnostic utilisant des ondes ultrasonores, sonores ou infrasonores

Abrégé

A miniature single-photon fluorescence microscope implantation device and implantation method are disclosed. The implantation device includes: a clamp base defining a clamp slot; a clamp block; and a groove defined in a bottom surface of the clamp slot. An end of the clamp block includes a first protrusion, and a bottom surface of the groove vertically defines a through receiving hole.

Classes IPC  ?

• A61B 90/14 - Instruments, outillage ou accessoires spécialement adaptés à la chirurgie ou au diagnostic non couverts par l'un des groupes , p.ex. pour le traitement de la luxation ou pour la protection de bords de blessures pour la chirurgie stéréotaxique, p.ex. système stéréotaxique à cadre - Détails de construction des fixateurs, p.ex. broches
• A61B 90/11 - Instruments, outillage ou accessoires spécialement adaptés à la chirurgie ou au diagnostic non couverts par l'un des groupes , p.ex. pour le traitement de la luxation ou pour la protection de bords de blessures pour la chirurgie stéréotaxique, p.ex. système stéréotaxique à cadre avec des guides pour aiguilles ou instruments, p.ex. des glissières courbes ou des articulations à rotule

Abrégé

The present application disclosed a magnetic levitation system, and the magnetic levitation system includes a stator, a rotor, and a magnetic coupling mechanism; the stator includes a stator winding mechanism for controlling the rotor to move away from or close to the axis direction of the stator. The magnetic coupling mechanism includes magnetic sources, and the magnetic coupling mechanism is magnetically coupled with the rotor through the magnetic sources to drive the rotor to rotate around the axis direction of the stator. The magnetic levitation system decouples the magnetic circuit that drives the rotor to move from the magnetic circuit that drives the rotor to rotate, so as to reduce control difficulty, enhance stability, and reduce torque fluctuations.

Classes IPC  ?

• H02K 7/09 - Association structurelle avec des paliers avec des paliers magnétiques
• H02K 1/17 - Noyaux statoriques à aimants permanents
• H02K 1/14 - Noyaux statoriques à pôles saillants
• H02K 11/21 - Dispositifs pour détecter la vitesse ou la position, ou actionnés par des valeurs de ces variables
• H02K 11/33 - Circuits d’entraînement, p.ex. circuits électroniques de puissance

Abrégé

A high-temperature-resistant insulating polymer composite is provided, including the following components in parts by mass: 3-12 parts of cyanate ester resin, 3-20 parts of epoxy resin, 5-15 parts of an inorganic filler, 0.1-2 parts of an epoxy resin curing agent, 0.0001-0.005 parts of a curing accelerant, and 0.1-2 parts of a dispersant. A glass transition temperature of the cured high-temperature-resistant insulating polymer composite is higher than 120° C.

Classes IPC  ?

• C08L 63/00 - Compositions contenant des résines époxy; Compositions contenant des dérivés des résines époxy
• C08G 59/24 - Composés diépoxydés carbocycliques
• C08G 59/28 - Composés diépoxydés contenant des atomes d'azote acycliques
• C08G 59/40 - Macromolécules obtenues par polymérisation à partir de composés contenant plusieurs groupes époxyde par molécule en utilisant des agents de durcissement ou des catalyseurs qui réagissent avec les groupes époxyde caractérisées par les agents de durcissement utilisés
• C08G 59/50 - Amines
• C08K 3/22 - Oxydes; Hydroxydes de métaux

Abrégé

A method and a system for generating a dynamic addictive neural circuit based on weakly supervised contrastive learning are disclosed. The method includes: based on a convolutional neural network, reducing a dimensionality of voxels of multiple groups of fMRI to attributes of brain region nodes, and generating multiple groups of dynamic brain connection maps containing time series based on the attributes of the brain region nodes; extracting spatio-temporal features of brain connections in the dynamic brain connection maps; inputting the spatio-temporal features into an abnormal connection detection network, calculating an abnormal probability of brain connections based on contrastive learning, and obtaining the brain connection with a highest abnormal probability at each time point; and generating the dynamic addictive neural circuit based on neuroscientific prior knowledge and the brain connection with the greatest probability of abnormality.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p.ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersections; Analyse de connectivité, p.ex. de composantes connectées
• G06V 10/62 - Extraction de caractéristiques d’images ou de vidéos relative à une dimension temporelle, p.ex. extraction de caractéristiques axées sur le temps; Suivi de modèle
• G06N 3/094 - Apprentissage antagoniste
• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne

Abrégé

Provided is a quad-core radio-frequency coil circuit. The quad-core radio-frequency coil circuit includes a coil module (1) and a front-end module (2). The coil module (1) is configured to receive a nuclear magnetic test signal and, according to the nuclear magnetic test signal, generate an induction signal. The front-end module (2) is connected to the coil module (1) and configured to generate the nuclear magnetic test signal and collect the induction signal.

Classes IPC  ?

• G01R 33/36 - Systèmes d'excitation ou de détection, p.ex. utilisant des signaux radiofréquence - Détails électriques, p.ex. adaptations ou couplage de la bobine au récepteur
• G01R 33/3415 - Systèmes d'excitation ou de détection, p.ex. utilisant des signaux radiofréquence - Détails de structure, p.ex. résonateurs comprenant des bobines de surface comprenant des ensembles de bobines

Abrégé

A brain network and brain addictive connectivity computing method and device are disclosed. The method includes: obtaining real brain functional magnetic resonance (fMRI) images associated with different labels; generating first brain topologies associated with the different labels based on at least one training real brain fMRI image sample; generating a brain addiction standard feature map based on an additive real brain fMRI image; determining an initial weight value of each of the first brain topologies according to the brain addiction standard feature map; training an addictive brain network analysis model based on the first brain topologies associated with different labels and the initial weight value of each first brain topology; inputting at least one testing real brain fMRI image sample into addictive brain network analysis model to generate first weighted brain topologies.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus

Abrégé

A biological sample sorting method, a surface acoustic wave microfluidic chip, a system, a terminal, and a storage medium are disclosed. The method includes: injecting a mixed solution containing biological samples into a surface acoustic wave microfluidic chip, and applying a first sinusoidal signal thereto forming a standing wave sound field therein to aggregate the biological samples; collecting images of the aggregated biological samples; performing moving target identification and tracking on the images of the biological samples using a deep learning model, performing cluster analysis and classification on a tracked moving target to obtain a target sample, and generating a delay enabling signal of the target sample according to a moving speed of the target sample; and applying a second sinusoidal signal to the surface acoustic wave microfluidic chip according to the delay enable signal to move the target sample thus sorting out the target sample.

Classes IPC  ?

• C12M 1/42 - Appareils pour le traitement de micro-organismes ou d'enzymes au moyen d'énergie électrique ou ondulatoire, p.ex. magnétisme, ondes sonores
• G06N 3/045 - Combinaisons de réseaux
• G06T 7/20 - Analyse du mouvement

Abrégé

A shimming method and device, an electronic device, and a storage medium are disclosed. The shimming method includes: obtaining object static magnetic field distribution information corresponding to a target object, the object static magnetic field distribution information including the static magnetic field distribution information of the target object under the action of a main magnet of a magnetic resonance system; determining a target static magnetic field based on the object static magnetic field distribution information and a preset shim coil magnetic field distribution model; and adjusting at least one shim coil parameter in the shim coil magnetic field distribution model until a magnetic field uniformity of the target static magnetic field satisfies a preset condition, and accordingly obtaining at least one target shim coil parameter.

Classes IPC  ?

• G01R 33/3875 - Compensation des inhomogénéités utilisant des ensembles de bobines de correction, p.ex. compensation active
• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique

Abrégé

Provided are composite array electrode, preparation method thereof and use thereof. The composite array electrode comprises a microelectrode array substrate, and a modification layer formed on a surface of a microelectrode of the microelectrode array substrate, wherein the modification layer comprises a plurality of electrically conductive layers arranged at intervals on the surface of the microelectrode, an insulating layer arranged on the surface of the microelectrode except the electrically conductive layers, and wherein material for the electrically conductive layers comprises one or more of nano platinum, nano iridium, conductive polymer and carbon nanotubes. The composite array electrode effectively eliminates the influence of edge effect such that the electric field distributes uniformly on the microelectrode surface of the composite array electrode, significantly improving electrochemical performance and detection capability of the electrode.

Classes IPC  ?

• C25D 7/12 - Semi-conducteurs
• A61B 5/268 - Détection, mesure ou enregistrement de signaux bioélectriques ou biomagnétiques du corps ou de parties de celui-ci Électrodes bioélectriques à cet effet caractérisées par les matériaux des électrodes contenant des polymères conducteurs, p.ex. des polymères PEDOT:PSS
• A61B 5/1468 - Mesure des caractéristiques du sang in vivo, p.ex. de la concentration des gaz dans le sang, de la valeur du pH du sang en utilisant des procédés chimiques ou électrochimiques, p.ex. par des moyens polarographiques
• B08B 3/08 - Nettoyage impliquant le contact avec un liquide le liquide ayant un effet chimique ou dissolvant
• B08B 7/02 - Nettoyage par des procédés non prévus dans une seule autre sous-classe ou un seul groupe de la présente sous-classe par distorsion, battage ou vibration de la surface à nettoyer
• C25D 5/02 - Dépôt sur des surfaces déterminées
• C25D 5/34 - Prétraitement des surfaces métalliques à revêtir de métaux par voie électrolytique
• G01N 27/327 - Electrodes biochimiques

Abrégé

A soft-bodied apparatus and a method for opening an eyelid are provided. The apparatus includes: a head support module, a real-time eyelid positioning module, a robot end-effector real-time positioning module, and an automatic eyelid opening operation module. The automatic eyelid opening operation module includes a robot body and a robot control system. The robot body is provided with a multi-axis rigid body mechanical arm and a soft-bodied end-effector. The robot control system takes the real-time poses of the upper and lower eyelids of the user as a motion target, and takes the real-time shape and the pose of the soft-bodied end-effector as feedback information to control motion of the robot body to automatically open the eyelid.

Classes IPC  ?

• A61B 17/02 - Instruments, dispositifs ou procédés chirurgicaux, p.ex. tourniquets Écarteurs
• A61F 9/007 - Procédés ou dispositifs pour la chirurgie de l'œil
• A61B 34/32 - Robots chirurgicaux opérant de façon autonome
• A61B 90/00 - Instruments, outillage ou accessoires spécialement adaptés à la chirurgie ou au diagnostic non couverts par l'un des groupes , p.ex. pour le traitement de la luxation ou pour la protection de bords de blessures

Abrégé

Methods and apparatuses for training a magnetic resonance imaging model, electronic devices and computer readable storage media are provided. A method may include: acquiring a magnetic resonance image data set; constructing a ring deep neural network to be trained; inputting an under-sampled magnetic resonance image and a full-sampled magnetic resonance image respectively to two neural networks included in the ring deep neural network, to generate respective simulated magnetic resonance images; inputting a first simulated full-sampled magnetic resonance image and the full-sampled magnetic resonance image to a pre-constructed first simulated magnetic resonance image class discrimination model, to obtain a first discrimination result indicating whether or not the first simulated full-sampled magnetic resonance image is of a simulated magnetic resonance image class; and adjusting a network parameter of the ring deep neural network based on a preset loss function, to obtain a trained magnetic resonance imaging model.

Classes IPC  ?

• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique
• G06V 10/42 - Extraction de caractéristiques globales par l’analyse du motif entier, p.ex. utilisant des transformations dans le domaine de fréquence ou d’autocorrélation
• G06T 11/00 - Génération d'images bidimensionnelles [2D]

Abrégé

A medical image noise reduction method, system, terminal and storage medium are disclosed. The method includes: obtaining a standard-dose PET image and a. constant-value image; inputting the standard-dose PET image and the constant-value image into a decay function to obtain a corresponding low-dose noisy PET image and a noisy constant-value image, respectively; assembling the low-dose noisy PET image and the noisy constant-value image in a width dimension or a height dimension, and then inputting into a trained conjugate generative adversarial network, and outputting a denoised PET image and constant-value image output by the conjugate generative adversarial network.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• G06V 10/776 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source Évaluation des performances
• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• G06V 10/77 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 10/40 - Extraction de caractéristiques d’images ou de vidéos
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo

Abrégé

An apriori guidance network for multitask medical image synthesis is provided. The apriori guidance network includes a generator and a discriminator, wherein the generator includes an apriori guidance module configured to convert an input feature map into a target modal image pointing to a target domain according to an apriori feature, and the apriori feature is a deep feature of the target modal image. The generator is configured to generate a corresponding target domain image by taking the apriori feature of the target modal image and source modal image data as an input. The discriminator is configured to discriminate an authenticity of the target domain image outputted by the generator.

Classes IPC  ?

• G06T 5/50 - Amélioration ou restauration d'image en utilisant plusieurs images, p.ex. moyenne, soustraction
• G06T 7/00 - Analyse d'image
• G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition

Abrégé

The present application provides a method and an apparatus for reconstructing a medical image, and a method and an apparatus for training a medical image reconstruction network. The method for training a medical image reconstruction network includes: performing feature coding extraction on a real image sample to obtain a feature coding vector of the real image sample; performing, through an image reconstruction network, image reconstruction based on the feature coding vector to obtain a first image, and performing image reconstruction based on a first hidden layer vector of the real image sample to obtain a second image; and performing, through an image discrimination network, image discrimination on the real image sample, the first image, and the second image, and optimizing the image reconstruction network according to an image discrimination result.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• G06V 10/776 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source Évaluation des performances
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 10/74 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques

Abrégé

An infrared image sequence-based sleep quality evaluation system and method. The method comprises: obtaining a plurality of respiratory infrared image sequences to be evaluated, one respiratory infrared image sequence comprising a plurality of respiratory infrared image frames to be evaluated; performing sleep quality evaluation on each respiratory infrared image sequence in the plurality of respiratory infrared image sequences by means of a classifier to obtain a sleep quality evaluation result corresponding to each respiratory infrared image sequence; and counting the number of different sleep quality evaluation results according to the sleep quality evaluation results respectively corresponding to the plurality of respiratory infrared image sequences, and determining the sleep quality evaluation result with the largest number as a sleep quality evaluation result of a user. Contactless sleep monitoring can be carried out on a user, monitoring costs are reduced at the same time, and evaluation accuracy of sleep quality is improved.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
• A61B 5/08 - Dispositifs de mesure pour examiner les organes respiratoires

Abrégé

The insulation adhesive film material is composed of a three-layer structure, its insulation polymer composite is supported by a thin film material, and a surface of the insulation polymer composite is covered with a layer of protective film. A release force of a support film is 25-60 μN/mm, and a release force of the protective film is 2-60 μN/mm. A thickness of the insulation polymer composite is 1-300 μm. The insulation adhesive film material is prepared as follows: after a high molecular polymer, an inorganic filler, a high molecular polymer curing agent, a molding auxiliary agent, and a solvent are mixed, dispersion technologies such as ball milling, sand milling, ultrasound are conducted to prepare an electronic paste of the insulation polymer composite, and the electronic paste is then applied to a surface of a support film material, and bonded with the protective film to form the insulation adhesive film material.

Classes IPC  ?

• C09J 7/30 - Adhésifs sous forme de films ou de pellicules caractérisés par la composition de l’adhésif
• B32B 27/36 - Produits stratifiés composés essentiellement de résine synthétique comprenant des polyesters
• B32B 27/32 - Produits stratifiés composés essentiellement de résine synthétique comprenant des polyoléfines
• B32B 27/08 - Produits stratifiés composés essentiellement de résine synthétique comme seul composant ou composant principal d'une couche adjacente à une autre couche d'une substance spécifique d'une résine synthétique d'une sorte différente
• B32B 7/06 - Liaison entre couches permettant une séparation sans difficultés
• B32B 37/24 - Procédés ou dispositifs pour la stratification, p.ex. par polymérisation ou par liaison à l'aide d'ultrasons caractérisés par les propriétés des couches avec au moins une couche qui ne présente pas de cohésion avant la stratification, p.ex. constituée de matériau granulaire projeté sur un substrat
• B32B 37/06 - Procédés ou dispositifs pour la stratification, p.ex. par polymérisation ou par liaison à l'aide d'ultrasons caractérisés par le procédé de chauffage
• C09J 7/25 - Matières plastiques; Matières plastiques métallisées à base de composés macromoléculaires obtenus par des réactions autres que celles faisant intervenir uniquement des liaisons non saturées carbone-carbone
• C09J 11/04 - Additifs non macromoléculaires inorganiques
• C09J 163/00 - Adhésifs à base de résines époxy; Adhésifs à base de dérivés des résines époxy

Abrégé

Disclosed by the present application are an image enhancement method and apparatus, a terminal device and a computer-readable storage medium. The image enhancement method comprises: obtaining an image to be processed; performing a wavelet transform operation on the image to obtain raw feature information of the image, the raw feature information comprising global contour feature information, transversal detail feature information, longitudinal detail feature information, and contrast detail feature information; inputting the raw feature information into a trained target network for processing to obtain corresponding reconstruction feature information, the reconstruction feature information comprising global contour reconstruction information, transversal detail reconstruction information, longitudinal detail reconstruction information, and contrast detail reconstruction information; performing an inverse wavelet transform operation on the reconstruction feature information to obtain a reconstructed image; the resolution of the reconstructed image is higher than the resolution of the image to be processed.

Classes IPC  ?

• G06T 5/10 - Amélioration ou restauration d'image en utilisant le filtrage dans le domaine non spatial
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

The present invention provides a magnetic sorting microfluidic chip, including a substrate, a chip model material layer, a micro-channel unit and a magnetic sorting unit, where the chip model material layer is disposed on the substrate, and the micro-channel unit and the magnetic sorting unit are both disposed in the chip model material layer; the micro-channel unit includes a sorting channel and magnetic pole channels; the sorting channel is provided with a plurality of sorting channel inlets and a plurality of sorting channel outlets; and the magnetic sorting unit includes permanent magnets, high-permeability alloys, and magnetic pole arrays disposed in the magnetic pole channels, where the high-permeability alloys are configured to conduct magnetic fields of the permanent magnets to the magnetic pole arrays, so that the magnetic pole arrays generate magnetic fields having opposite polarities on left and right positions of the sorting channel.

Classes IPC  ?

• B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes
• B33Y 80/00 - Produits obtenus par fabrication additive

Abrégé

A flexible radiofrequency receiving coil array. The flexible radiofrequency receiving coil array is provided on a flexible panel and comprises several rows of coil units. Adjacent two rows of coil units in the several rows of coil units are alternately arranged. Preamplifiers are provided in the coil units. In the flexible radiofrequency receiving coil array, two preamplifiers in adjacent two coil units are provided on a same preamplifier mounting plate on the flexible panel, where multiple preamplifier mounting plates are provided on the flexible panel, and the preamplifier mounting plates of different columns and rows are linearly arranged. The flexible radiofrequency receiving coil array effectively reduces the distribution density of the preamplifiers, ensures the flexibility and maximum degree of distension of the coil array, and improves the fit of the coil array to the human body, thus increasing image signal-to-noise ration and image quality.

Classes IPC  ?

• G01R 33/36 - Systèmes d'excitation ou de détection, p.ex. utilisant des signaux radiofréquence - Détails électriques, p.ex. adaptations ou couplage de la bobine au récepteur
• G01R 33/34 - Systèmes d'excitation ou de détection, p.ex. utilisant des signaux radiofréquence - Détails de structure, p.ex. résonateurs

Abrégé

The present application is suitable for use in the technical field of computers, and provides a smart diagnosis assistance method and terminal based on medical images, comprising: acquiring a medical image to be classified; pre-processing the medical image to be classified to obtain a pre-processed image; and inputting the pre-processed image into a trained classification model for classification processing to obtain a classification type corresponding to the pre-processed image, the classification model comprising tensorized network layers and a second-order pooling module. As the trained classification model comprises tensor decomposed network layers and a second-order pooling module, when processing images on the basis of the classification model, more discriminative features related to pathologies can be extracted, increasing the accuracy of medical image classification.

Classes IPC  ?

• G06V 10/80 - Fusion, c. à d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06V 10/20 - Prétraitement de l’image
• G06T 7/00 - Analyse d'image
• G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition

Abrégé

A secondary battery and a method for making the same are disclosed. The secondary battery includes a battery negative electrode, an electrolyte liquid, a diaphragm and a battery positive electrode. The battery negative electrode includes a negative electrode current collector, which also acts as a negative electrode active material. The electrolyte liquid includes an electrolyte and a solvent, the electrolyte being a lithium salt. The battery positive electrode includes a positive electrode current collector and a positive electrode active material layer, which includes a positive electrode active material capable of reversibly de-intercalating lithium ions.

Classes IPC  ?

• H01M 10/0525 - Batteries du type "rocking chair" ou "fauteuil à bascule", p.ex. batteries à insertion ou intercalation de lithium dans les deux électrodes; Batteries à l'ion lithium
• H01M 10/0567 - Matériaux liquides caracterisés par les additifs
• H01M 4/505 - Emploi de substances spécifiées comme matériaux actifs, masses actives, liquides actifs d'oxydes ou d'hydroxydes inorganiques de manganèse d'oxydes ou d'hydroxydes mixtes contenant du manganèse pour insérer ou intercaler des métaux légers, p.ex. LiMn2O4 ou LiMn2OxFy
• H01M 4/525 - Emploi de substances spécifiées comme matériaux actifs, masses actives, liquides actifs d'oxydes ou d'hydroxydes inorganiques de nickel, de cobalt ou de fer d'oxydes ou d'hydroxydes mixtes contenant du fer, du cobalt ou du nickel pour insérer ou intercaler des métaux légers, p.ex. LiNiO2, LiCoO2 ou LiCoOxFy
• H01M 4/58 - Emploi de substances spécifiées comme matériaux actifs, masses actives, liquides actifs de structures polyanioniques, p.ex. phosphates, silicates ou borates
• H01M 4/66 - Emploi de matériaux spécifiés
• H01M 10/0568 - Matériaux liquides caracterisés par les solutés
• H01M 10/0569 - Matériaux liquides caracterisés par les solvants
• H01M 4/36 - Emploi de substances spécifiées comme matériaux actifs, masses actives, liquides actifs
• H01M 4/485 - Emploi de substances spécifiées comme matériaux actifs, masses actives, liquides actifs d'oxydes ou d'hydroxydes inorganiques d'oxydes ou d'hydroxydes mixtes pour insérer ou intercaler des métaux légers, p.ex. LiTi2O4 ou LiTi2OxFy
• H01M 4/80 - Plaques poreuses, p.ex. supports frittés
• H01M 4/1395 - Procédés de fabrication d’électrodes à base de métaux, de Si ou d'alliages
• H01M 4/46 - Alliages à base de magnésium ou d'aluminium
• H01M 4/134 - PROCÉDÉS OU MOYENS POUR LA CONVERSION DIRECTE DE L'ÉNERGIE CHIMIQUE EN ÉNERGIE ÉLECTRIQUE, p.ex. BATTERIES Électrodes Électrodes composées d'un ou comprenant un matériau actif Électrodes pour accumulateurs à électrolyte non aqueux, p.ex. pour accumulateurs au lithium; Leurs procédés de fabrication Électrodes à base de métaux, de Si ou d'alliages
• H01M 10/0585 - Structure ou fabrication d'accumulateurs ayant uniquement des éléments de structure plats, c. à d. des électrodes positives plates, des électrodes négatives plates et des séparateurs plats
• H01M 50/44 - Matériau fibreux
• H01M 50/409 - Séparateurs, membranes ou diaphragmes caractérisés par le matériau
• H01M 50/411 - Matériau organique
• H01M 50/431 - Matériau inorganique
• H01M 4/62 - Emploi de substances spécifiées inactives comme ingrédients pour les masses actives, p.ex. liants, charges
• H01M 10/058 - Structure ou fabrication

Abrégé

A closed-loop artificial pancreas system based on a wearable monitoring method is provided. The system includes: a wearable blood glucose monitoring submodule, configured to obtain a blood glucose sensing signal in a noninvasive manner by utilizing a wearable device; a diet and exercise monitoring submodule, configured to obtain diet monitoring data and exercise monitoring data which can cause variations of blood glucose concentration of a subject to be tested; a calculation control submodule, configured to obtain information related to insulin infusion by utilizing a trained deep learning model, the diet monitoring data, and the exercise monitoring data; an insulin infusion submodule, configured to automatically implement insulin infusion; and an effect assessment module, configured to assess an insulin infusion effect, and to feed an assessment result back to the calculation control submodule, such that the calculation control submodule determines whether to update the information related to insulin infusion.

Classes IPC  ?

• A61M 5/172 - Moyens pour commander l'écoulement des agents vers le corps ou pour doser les agents à introduire dans le corps, p.ex. compteurs de goutte-à-goutte électriques ou électroniques
• G16H 40/63 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santé; TIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement local
• G16H 20/17 - TIC spécialement adaptées aux thérapies ou aux plans d’amélioration de la santé, p.ex. pour manier les prescriptions, orienter la thérapie ou surveiller l’observance par les patients concernant des médicaments ou des médications, p.ex. pour s’assurer de l’administration correcte aux patients administrés par perfusion ou injection
• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux

Abrégé

A method, device and equipment for reconstructing a PET image are provided. The method includes acquiring a prior image comprising an anatomical image and an autocorrelation feature image, the autocorrelation feature image being determined based on gray-level co-occurrence matrix of the anatomical image; and acquiring a feature value of the prior image; reconstructing the PET image according to the feature value and an iterative algorithm.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• A61B 6/03 - Tomographes assistés par ordinateur
• G06V 10/77 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source

Abrégé

A prediabetes detection system and method based on combination of electrocardiogram and electroencephalogram information are provided. The system includes: a signal obtaining module, configured to obtain an electrocardiogram signal and an electroencephalogram signal of a user in a noninvasive manner; a feature extraction module, configured to: perform dimension reduction processing on a combined feature set composed of an electrocardiogram feature and an electroencephalogram feature to obtain a plurality of dimension-reduced combined feature sets, and select an electrocardiogram feature and an electroencephalogram feature meeting a preset criteria of correlation by analyzing a correlation between the plurality of dimension-reduced combined feature sets and a blood glucose concentration value to constitute an optimized combined feature set; and a multimodal fusion module, configured to input the optimized combined feature set into a plurality of trained neural network models, to obtain a detection result by fusing results of the plurality of neural networks.

Classes IPC  ?

• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
• A61B 5/349 - Détection de paramètres spécifiques du cycle de l'électrocardiogramme
• A61B 5/374 - Détection de la répartition de fréquence dans les signaux, p.ex. détection des ondes delta, thêta, alpha, bêta ou gamma
• A61B 5/256 - Moyens pour maintenir le contact de l’électrode avec le corps Électrodes portables, p.ex. avec des sangles ou des bandes
• A61B 5/291 - Détection, mesure ou enregistrement de signaux bioélectriques ou biomagnétiques du corps ou de parties de celui-ci Électrodes bioélectriques à cet effet spécialement adaptées à des utilisations particulières pour l’électroencéphalographie [EEG]
• A61B 5/28 - Détection, mesure ou enregistrement de signaux bioélectriques ou biomagnétiques du corps ou de parties de celui-ci Électrodes bioélectriques à cet effet spécialement adaptées à des utilisations particulières pour l’électrocardiographie [ECG]
• A61B 5/145 - Mesure des caractéristiques du sang in vivo, p.ex. de la concentration des gaz dans le sang, de la valeur du pH du sang
• A61B 5/0205 - Evaluation simultanée de l'état cardio-vasculaire et de l'état d'autres parties du corps, p.ex. de l'état cardiaque et respiratoire

Abrégé

The invention provides a stepping doser. The doser comprises a bearing component, a dosing catheter, wiring tubes, a threaded rod, a nut, a signal recorder and a connecting rod; wherein the middle socket of the threaded rod is sheathed with a nut, the lower end of the threaded rod contacts the lower inner wall of the bearing component, the upper end of the threaded rod penetrates the upper part of the bearing component, and the upper end of the threaded rod is provided with a driving structure; The bearing component is also provided with a limit stop for limiting the rotation of the nut so that when the threaded rod rotates, the nut can move up and down; when the nut moves up and down, the dosing catheter can move up and down. The dosing catheter can be stepped with this doser, allowing dosing in a larger area.

Classes IPC  ?

• A61D 7/00 - Dispositifs ou méthodes pour l'introduction de remèdes, solides, liquides ou gazeux ou d'autres produits dans ou sur le corps des animaux
• A61B 5/291 - Détection, mesure ou enregistrement de signaux bioélectriques ou biomagnétiques du corps ou de parties de celui-ci Électrodes bioélectriques à cet effet spécialement adaptées à des utilisations particulières pour l’électroencéphalographie [EEG]
• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus

Abrégé

A method for processing positron emission tomography data is provided, this method includes: obtaining a first coordinate and a second coordinate respectively corresponding to two ends of a response line to be processed; determining corresponding dimensional coordinates of the response line to be processed in a sinogram based on the first coordinate and the second coordinate; and generating the sinogram corresponding to the response line to be processed based on the dimensional coordinates. According to this method, the amount of calculation of system matrix is reduced, the accuracy of position information of the generated response line is improved, and the accuracy of generated sinogram is improved accordingly.

Classes IPC  ?

• G01T 1/29 - Mesure effectuée sur des faisceaux de radiations, p.ex. sur la position ou la section du faisceau; Mesure de la distribution spatiale de radiations
• A61B 6/03 - Tomographes assistés par ordinateur

Abrégé

A medical image processing method and processing apparatus, and a computer readable storage medium. The method includes: obtaining a to-be-processed image; performing a feature extraction on the to-be-processed image to obtain a corresponding feature image; and re-determining a pixel value of each pixel in the to-be-processed image based on first information and second information of a corresponding pixel in the feature image, and processing the to-be-processed image; wherein the first information is information of a pixel adjacent to the corresponding pixel in the features image, and the second information is information of a pixel that is not adjacent to and is similar to the corresponding pixel in the features image.

Classes IPC  ?

• G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
• G06V 10/75 - Appariement de motifs d’image ou de vidéo; Mesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexte; Sélection des dictionnaires
• G06T 5/00 - Amélioration ou restauration d'image
• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

The present invention describes a system and method for selecting and optimizing a sound stimulus using a deep neural network to regulate and improve human sleep quality. The deep neural network has the capability of characterizing processing of human brain cortical neurons for external stimulus (images, sounds, etc.) information. By inputting massive sound stimuli into the deep neural network, a sound mode which causes model-estimated sleep electroencephalograph to be optimal can be found, the sound mode is applied to a real human body, and the intensity of corresponding sleep waves of the human body in different sleep stages is enhanced through closed-loop optimization so as to realize the purpose of regulating sleep. The present invention mainly aims at solving the technical problem of how to select and optimize, when a sound stimulus means (music, speech, natural sounds, white/colored noise, etc.) is used to assist in human sleep.

Classes IPC  ?

• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
• A61B 5/374 - Détection de la répartition de fréquence dans les signaux, p.ex. détection des ondes delta, thêta, alpha, bêta ou gamma
• A61B 5/291 - Détection, mesure ou enregistrement de signaux bioélectriques ou biomagnétiques du corps ou de parties de celui-ci Électrodes bioélectriques à cet effet spécialement adaptées à des utilisations particulières pour l’électroencéphalographie [EEG]

Abrégé

The present invention provides a panoramic presentation method and apparatus. The present invention presents a panoramic image by using a combined structure of a single fisheye projector and a spherical screen in hardware, employs a geometrical relationship between a fisheye lens and the position of a viewer and isometric projection transformation, and enables 180° fisheye projection to present 720° environment information to the viewer in the center of the spherical screen, greatly simplifying the image conversion process and realizing zero distortion. According to a 720° panorama one-step generation method based on a single virtual camera in software, complex steps of collecting six images by a plurality of cameras, synthesizing a cube map and then converting the cube map into a panorama are not needed, the vertex position of a scene is directly adjusted in the process from a 3D space to a 2D image

Classes IPC  ?

• G06T 3/40 - Changement d'échelle d'une image entière ou d'une partie d'image
• G06T 3/00 - Transformation géométrique de l'image dans le plan de l'image
• G03B 37/04 - Photographie panoramique ou à grand écran; Photographie de surfaces étendues, p.ex. pour la géodésie; Photographie de surfaces internes, p.ex. de tuyaux avec appareils ou projecteurs qui permettent la juxtaposition ou le recouvrement partiel des champs de vision

Abrégé

A method for denoising an image, an apparatus, and a computer-readable storage medium. The method includes: dividing a to-be-processed image into a plurality of image areas; for each image area, expanding an edge of the image area to obtain an expanded area; wherein the expanded area comprises the image area and an edge area, and the edge area comprises pixels in another image area adjacent to the image area; for each expanded area, performing denoising processing on the expanded area through a preset algorithm to obtain a denoised expanded area; wherein the denoised expanded area comprises a denoised image area and a denoised edge area; and abandoning the denoised edge area in each denoised expanded area, and retaining and combining all the denoised image areas to form a denoised image.

Classes IPC  ?

• G06T 5/00 - Amélioration ou restauration d'image
• G06T 5/50 - Amélioration ou restauration d'image en utilisant plusieurs images, p.ex. moyenne, soustraction

Abrégé

A method and an apparatus for generating time series data based on multi-condition constraints, and a medium are provided. The method include the following: a data repair request from a client is received, the data repair request including to-be-repaired data and condition information; normalization processing is performed on the to-be-repaired data to obtain normalized data, and tensor processing is performed on the condition information to obtain a feature label; a trained data repair model is called to perform repair processing on the normalized data according to the feature label to obtain first repaired data, the data repair model being obtained by training according to sample data, a first sample condition, real sample data and a second sample condition, and the sample data being noise data; and the first repaired data is sent to the client. By adopting embodiments of the application, rich features of the data can be acquired without a large amount of historical data or sample data with high matching degree as training basis, thus ensuring the accuracy and timing of the repaired data, and improving the repair efficiency and quality.

Classes IPC  ?

• G06F 11/00 - Détection d'erreurs; Correction d'erreurs; Contrôle de fonctionnement
• G06F 11/07 - Réaction à l'apparition d'un défaut, p.ex. tolérance de certains défauts

Abrégé

A method for preparing a flexible electrode is provided. The method comprises sequentially forming a flexible base layer and an intermediate conductive layer on a carrier plate; treating an elastomeric template having an electrode pattern with an acid, followed by transferring and printing the electrode pattern onto the intermediate conductive layer to form an electrode inducing layer; forming a titanium dioxide-polydopamine composite layer in a gap of the electrode inducing layer; forming a platinum electrode layer on the titanium dioxide-polydopamine composite layer; removing the carrier plate. The invention solves the problems of slow formation of a polydopamine film and slow formation of a platinum electrode layer. A flexible electrode is further provided.

Classes IPC  ?

• B81C 1/00 - Fabrication ou traitement de dispositifs ou de systèmes dans ou sur un substrat
• B81B 3/00 - Dispositifs comportant des éléments flexibles ou déformables, p.ex. comportant des membranes ou des lamelles élastiques

Abrégé

A method and an apparatus for determining a service area of a parking lot, a device and a storage medium are provided. The method includes the following: clustering is performed on all first parking lots to obtain at least one second parking lot set according to an initial weight and initial position information of each first parking lot in a first parking lot set; a transition probability matrix corresponding to each second parking lot in each second parking lot set is determined according to the initial weight and the initial position information, where a transition probability in the transition probability matrix is used for indicating a probability that a parking user transfers to another second parking lot in the same second parking lot set when there is no empty parking space in the second parking lot; and a service capacity value of each second parking lot is determined.

Classes IPC  ?

• G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
• G08G 1/14 - Systèmes de commande du trafic pour véhicules routiers indiquant des places libres individuelles dans des parcs de stationnement
• G07B 15/02 - Dispositions ou appareils pour encaisser le prix des billets ou les droits d’entrée ou de péage en un ou plusieurs points de contrôle prenant en compte un facteur variable tel que la distance ou le temps, p.ex. pour le transport de passagers, les systèmes de parcs de stationnement ou les systèmes de location de véhicules

Abrégé

The present application relates to a method and system for generating multi-task learning-type generative adversarial network for low-dose PET reconstruction, and relates to the field of deep learning. The method includes connecting layers of the encoder with layers of the decoder by skip connection to provide a U-Net type picture generator; generating a group of generative adversarial networks by matching a plurality of picture generators with a plurality of discriminators in one-to-one manner; obtaining a first multi-task learning-type generative adversarial network; designing a joint loss function 1 for improving image quality; and training the first multi-task learning-type generative adversarial network according to the joint loss function 1 in combination with an optimizer to provide a second multi-task learning-type generative adversarial network.

Classes IPC  ?

• G06T 5/00 - Amélioration ou restauration d'image
• A61B 6/03 - Tomographes assistés par ordinateur
• G06N 3/08 - Méthodes d'apprentissage
• G06N 3/045 - Combinaisons de réseaux

Abrégé

Provided is a micro- and nano-fluidic chip, including at least one nanochannel array layer and at least one microchannel array layer that are alternately stacked. The at least one nanochannel array layer includes nanochannels, the at least one microchannel array layer includes input units and/or output units. The input unit includes inlet microchannel arrays and inlets, and the output unit includes outlet microchannel arrays and outlets. The inlet microchannel array includes inlet microchannels, the outlet microchannel array includes outlet microchannels, and the inlet microchannels and the outlet microchannels are connected through the nanochannels.

Classes IPC  ?

• B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes
• G03F 7/38 - Traitement avant le dépouillement selon l'image, p.ex. préchauffage
• G03F 7/039 - Composés macromoléculaires photodégradables, p.ex. réserves positives sensibles aux électrons
• G03F 7/20 - Exposition; Appareillages à cet effet
• G03F 7/40 - Traitement après le dépouillement selon l'image, p.ex. émaillage
• G03F 7/32 - Compositions liquides à cet effet, p.ex. développateurs
• G03F 7/038 - Composés macromoléculaires rendus insolubles ou sélectivement mouillables
• A61K 45/06 - Mélanges d'ingrédients actifs sans caractérisation chimique, p.ex. composés antiphlogistiques et pour le cœur 

Abrégé

A ranking method of urban parking lots based on temporal and spatial features and its device, terminal and medium, wherein the method comprises: adopting service capability model and temporal-spatial transition model to get the initial service capability ranking of all parking lots and the transition probability matrix between parking lots at the moment based on all parking lots within the preset urban regions and their static and dynamic information; using the power iteration algorithm to iteratively calculate the comprehensive service capability ranking of all parking lots at the moment in accordance with initial service capability ranking and transition probability matrix until the stopping conditions for the iteration are met; sequencing the parking lots based on comprehensive service capability ranking, thus achieving real-time quantitative computation of service capability of any urban parking lot from the temporal and spatial dimensions

Classes IPC  ?

• G06Q 50/30 - Transport; Communications
• G08G 1/14 - Systèmes de commande du trafic pour véhicules routiers indiquant des places libres individuelles dans des parcs de stationnement
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06F 17/18 - Opérations mathématiques complexes pour l'évaluation de données statistiques

Abrégé

An image feature visualization method and apparatus, and an electronic device during model training, inputs the real training data with positive samples into a mapping generator to obtain fictitious training data with negative samples. The mapping generator includes a mapping module configured to learn a key feature map that distinguishes the real training data with positive samples/negative samples, and the fictitious training data with negative samples is generated based on the real training data with positive samples and the key feature map. The training data with negative samples is input into a discriminator to obtain a discrimination result. An optimizer optimizes the mapping generator and the discriminator until training is completed. During model application, a target image that is to be processed is input into the mapping generator, and the mapper in the mapping generator extracts features of the target image.

Classes IPC  ?

• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”
• G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06T 7/00 - Analyse d'image

Abrégé

The present application discloses a mitochondrion/ribonucleic acid-targeted and migratable photosensitized probe and application thereof. The mitochondrion/ribonucleic acid-targeted and migratable photosensitized probe has a structure represented by the following Formula I: The present application discloses a mitochondrion/ribonucleic acid-targeted and migratable photosensitized probe and application thereof. The mitochondrion/ribonucleic acid-targeted and migratable photosensitized probe has a structure represented by the following Formula I: The present application discloses a mitochondrion/ribonucleic acid-targeted and migratable photosensitized probe and application thereof. The mitochondrion/ribonucleic acid-targeted and migratable photosensitized probe has a structure represented by the following Formula I: where, R1 is selected from hydrogen or methyl; R2 is any one of selected from C1-C5 alkoxys; R3 is selected from methyl or hydroxymethyl; and X is selected from a halogen atom, BF4, or ClO4.

Classes IPC  ?

• A61K 41/00 - Préparations médicinales obtenues par traitement de substances par énergie ondulatoire ou par rayonnement corpusculaire
• A61K 49/00 - Préparations pour examen in vivo
• A61P 35/00 - Agents anticancéreux

Abrégé

A visualization method for evaluating brain addiction traits, an apparatus, and a computer-readable storage medium are provided. The method includes the following. A visualization processing request is received from a client, where the visual processing request contains an image to-be-processed. The image to-be-processed is masked to obtain a perturbation image masked. The perturbation image is classified with a visualization processing model to obtain a classification result, and the classification result is calculated to obtain an evaluation value of the perturbation image, where the evaluation value of the perturbation image is less than an evaluation value of the image to-be-processed without masking. The visualization evaluation result is determined according to the evaluation value of the perturbation image. The visualization evaluation result is sent to the client.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p.ex. des objets vidéo
• G06V 10/774 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p.ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]; Séparation aveugle de source méthodes de Bootstrap, p.ex. "bagging” ou “boosting”

Abrégé

An adversarial image generation method, a computer device, and a computer-readable storage medium are provided. The method includes the following. A reference model classification-equivalent with a target classification model is generated according to the target classification model. A target image is obtained and an original noise for the target image is generated according to the reference model. A first noise and the original noise are input into an adversarial model and a second noise corresponding to the first noise is output when the adversarial model meets a convergence condition, where the second noise enhances an information entropy of the original noise. An enhanced noise image corresponding to the target image is generated according to the second noise and the target image, where a classification accuracy of the enhanced noise image in the target classification model is less than a classification accuracy of the target image in the target classification model.

Classes IPC  ?

• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06F 21/36 - Authentification de l’utilisateur par représentation graphique ou iconique

Abrégé

A prediction method, device, equipment, and storage medium for the image-level JND threshold, comprising: perceptual distortion discrimination is conducted on the raw image and on the compressed images in the compressed image set of the said image through trained multi-class perceptual distortion discriminator to obtain the set of perceptual distortion discrimination results (S101), and preset image-level JND search strategies are adopted for fault tolerance of the said set of perceptual distortion discrimination results to predict the image-level JND threshold of the said image (S102), thus reducing the prediction deviation of the image-level JND threshold, improving the prediction accuracy of the image-level JND threshold, and bringing the predicted JND threshold closer to the human visual system's perception of the quality of the entire image.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
• G06T 7/11 - Découpage basé sur les zones
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion

Abrégé

An ultrasound guided puncture device and an ultrasound guided puncture apparatus are disclosed. The ultrasound guided puncture device includes a puncture needle tube and an ultrasound transducer. One end of the puncture needle tube has a puncture needle head, and the ultrasonic transducer is housed in the puncture needle tube and extends to the puncture needle head. The ultrasonic transducer includes multiple ultrasonic array elements for transmitting and receiving ultrasonic waves, and the multiple ultrasonic array elements are arranged at the puncture needle head. In actual use, electronic scanning imaging is performed through the multiple ultrasound array elements, hence a wide imaging range. It can effectively recognize the structure of the tissue in front of the puncture needle head, thereby facilitating the planning of the best puncture path.

Classes IPC  ?

• A61B 17/34 - Trocarts; Aiguilles à ponction

Abrégé

A friend recommendation method oriented towards subway passengers is disclosed, including: obtaining the source data associated with subway station passengers and subway operation; preprocessing the obtained source data; estimating passenger travel paths according to the preprocessed source data; calculating a detailed train operation timetable based on the subway train timetable and train departure intervals; matching each passenger to a specific train based on the estimated passenger travel paths and calculated train operation timetable; and extracting and measuring the interactions between passengers based on the matched passengers and specific trains, and accordingly making a friend recommendation. A friend recommendation system oriented towards subway passengers is further disclosed.

Classes IPC  ?

• G06Q 50/00 - Systèmes ou procédés spécialement adaptés à un secteur particulier d’activité économique, p.ex. aux services d’utilité publique ou au tourisme
• G06Q 50/26 - Services gouvernementaux ou services publics
• G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projets; Planification d’entreprise ou d’organisation; Modélisation d’entreprise ou d’organisation
• G06Q 30/02 - Marketing; Estimation ou détermination des prix; Collecte de fonds
• G06F 16/2455 - Exécution des requêtes
• B61L 15/00 - Indicateurs de signalisation sur le véhicule ou sur le train

Abrégé

The gene transfection system includes an acoustothermal module and a signal generating module; the acoustothermal module includes a piezoelectric substrate, an acoustothermal chip arranged on the piezoelectric substrate and N sound-absorbing vessels arranged on the acoustothermal chip and used for cultivating recipient cells, and N is an integer greater than or equal to 1; the signal generating module is used to output basic frequency signals; the acoustothermal chip is used to convert the basic frequency signal to an acoustic wave signal, establish a temperature gradient field with the acoustic wave signal, and control the temperature of the recipient cell in the sound-absorbing vessels with the temperature gradient field, so that the pores are opened on the membranes of the recipient cell, and the nucleic acids or other substances can go into the cells through these pores.

Classes IPC  ?

• C12N 15/87 - Introduction de matériel génétique étranger utilisant des procédés non prévus ailleurs, p.ex. co-transformation
• B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes

Abrégé

A non-redundant gene set clustering method and system, as well as an electronic device are disclosed. The method includes: operation a: performing an alignment operation on an original gene set to obtain gene pairs in the original gene set that meet a similarity threshold; operation b: constructing a union-find forest based on the obtained gene pairs; operation c: obtaining gene clustering results of all classes in the original gene set based on the union-find forest; and operation d: based on the gene clustering results, selecting the longest sequence in each class as a representative sequence of the class to obtain a non-redundant reference gene set. According to this application, the non-redundant gene set clustering is performed by using BLAT alignment and based on the disjoint-set data structure, and so can take into account the similarity between more genes and improve the accuracy of de-redundancy.

Classes IPC  ?

• G16B 20/00 - TIC spécialement adaptées à la génomique ou protéomique fonctionnelle, p. ex. corrélations génotype-phénotype
• G16B 40/00 - TIC spécialement adaptées aux biostatistiques; TIC spécialement adaptées à l’apprentissage automatique ou à l’exploration de données liées à la bio-informatique, p.ex. extraction de connaissances ou détection de motifs

Abrégé

A multi-row ultrasonic imaging apparatus and an ultrasonic imaging instrument are disclosed. The multi-row ultrasonic imaging apparatus includes a housing, and a first ultrasonic transducer, a second ultrasonic transducer, and an adjustment mechanism that are installed in the housing. Ultrasonic waves emitted by the first ultrasonic transducer and the second ultrasonic transducer can intersect to form a confocal point. At least one of the first ultrasonic transducer and the second ultrasonic transducer is connected to the adjustment mechanism to move relative to the housing under the action of the adjustment mechanism, so as to adjust the position of the confocal point.

Classes IPC  ?

• A61B 8/00 - Diagnostic utilisant des ondes ultrasonores, sonores ou infrasonores

Abrégé

An eddy-current correction method and apparatus, a mobile terminal and a readable storage medium are provided. The method includes: step S1: reading gradient-recalled echo sequence by means of bipolarity, so as to acquire a multi-echo image; step S2: estimating a first-order term coefficient of an extra phase term introduced by an eddy-current in the acquired multi-echo image; step S3: removing the estimated first-order term coefficient, and estimating a zero-order term coefficient of the extra phase term introduced by the eddy-current in the collected multi-echo image; step S4: removing, according to the estimated first-order term coefficient and the zero-order term coefficient, an error of the extra phase term introduced by the eddy-current. The eddy-current correction method removes the phase error caused by the eddy-current in the acquired image, thereby ensuring the correctness of the subsequent water-fat separation algorithm result.

Classes IPC  ?

• G01R 33/565 - Correction de distorsions d'image, p.ex. dues à des inhomogénéités de champ magnétique
• G01R 33/561 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne par réduction du temps de balayage, c.à d. systèmes d'acquisition rapide, p.ex. utilisant des séquences d'impulsions écho-planar
• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne
• G01R 33/48 - Systèmes d'imagerie RMN

Abrégé

A peptide for regulating fat metabolism is described. The peptide is selected from the group consisting of: YLGASVPSPDPLEP (SEQ ID NO: 1); YLNNGLGAPAPYPDPLEP (SEQ ID NO: 4); PDPLEP (SEQ ID NO: 14); and PSPDPLEP (SEQ ID NO: 16).

Classes IPC  ?

• C07K 7/08 - Peptides linéaires ne contenant que des liaisons peptidiques normales ayant de 12 à 20 amino-acides
• A61K 38/00 - Préparations médicinales contenant des peptides
• A61P 1/16 - Médicaments pour le traitement des troubles du tractus alimentaire ou de l'appareil digestif des troubles de la vésicule biliaire ou du foie, p.ex. protecteurs hépatiques, cholagogues, cholélitholytiques
• A61P 3/00 - Médicaments pour le traitement des troubles du métabolisme
• A61P 3/04 - Anorexigènes; Médicaments de l'obésité
• A61P 3/06 - Antihyperlipémiants
• A61P 3/10 - Médicaments pour le traitement des troubles du métabolisme de l'homéostase du glucose de l'hyperglycémie, p.ex. antidiabétiques

Abrégé

The present invention discloses a PET image reconstruction method, a computer storage medium, and a computer device. The method includes: step 1, obtaining projection data Y and a system matrix P of a PET image; step 2, constructing an imaging model equation Y=PX, in which X is a reconstructed PET image; step 3, obtaining the initial reconstructed image X, and iteratively updating the initial reconstructed image X according to a first objective function to obtain a first reconstructed image; step 4, iteratively updating the first reconstructed image according to the second objective function to obtain the second reconstructed image; and step 5, determining whether an iteration condition is satisfied, if yes, outputting the current round of iteration to obtain the second reconstructed image as a final PET reconstructed image, and if not, returning to step 3 and using the second reconstructed image in the current round of iteration as an initial reconstructed image in the next round of iteration. The reconstruction algorithm of the present invention does not depend on a conformity degree between anatomical structure information and functional information, and can distinguish image edges well regardless of whether there is noise interfering with the image edges.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• G06T 5/00 - Amélioration ou restauration d'image
• G06T 7/11 - Découpage basé sur les zones
• A61B 6/03 - Tomographes assistés par ordinateur

Abrégé

There are provided a parallel rapid imaging method and device based on a complex number conjugate symmetry of multi-channel coil data and nonlinear GRAPPA image reconstruction, and a medium. The imaging method includes: obtaining virtual conjugate coil data by expanding the actual multi-channel coil data; combining actual multi-channel coil data and virtual multi-channel coil data to obtain a linear data term and a nonlinear data term; calibrating weighting factors of the linear data term and the nonlinear data term by using combined low-frequency full-sampling data (margins of the low-frequency full-sampling data includes parts of high-frequency data); reconstructing data which is under-sampled in a high-frequency region according to the calibrated weighting factors; fusing the low-frequency full-sampling data and the reconstructed data for the high-frequency region.

Classes IPC  ?

• G01V 3/00 - Prospection ou détection électrique ou magnétique; Mesure des caractéristiques du champ magnétique de la terre, p.ex. de la déclinaison ou de la déviation
• G01R 33/561 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne par réduction du temps de balayage, c.à d. systèmes d'acquisition rapide, p.ex. utilisant des séquences d'impulsions écho-planar
• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne
• G01R 33/58 - Etalonnage des systèmes d'imagerie, p.ex. utilisant des sondes d'essai

Abrégé

A method for training a dialog generation model includes: acquiring a dialog data set, and encoding a post in the dialog data set by using an encoder in the dialog generation model to obtain an encoded representation of the post; fusing, by using a decoder in the dialog generation model, the encoded representation of the post and knowledge information corresponding to the post that is obtained from a knowledge base question answering model through transfer learning to obtain a predicted response corresponding to the post; determining a value of a loss function of the dialog generation model based on the predicted response and the annotated response that correspond to the post; and updating a model parameter of the dialog generation model based on the value of the loss function. A method, an apparatus, a device, and a computer storage medium for generating a dialog are also provided.

Classes IPC  ?

• G06F 40/35 - Représentation du discours ou du dialogue
• G06N 3/045 - Combinaisons de réseaux
• G06N 3/08 - Méthodes d'apprentissage
• G06N 5/04 - Modèles d’inférence ou de raisonnement

Abrégé

Disclosed are a magnetic-resonance imaging method, apparatus and system, and a storage medium. The method includes acquiring an initial model of magnetic-resonance imaging and establishing an initial imaging model according to an iterative algorithm used for solving the initial model, where the iterative algorithm includes at least one of an undetermined parameter, an undetermined solving operator or an undetermined structural relationship; training the initial imaging model on the basis of sample data to generate a magnetic-resonance imaging model, where training of the initial imaging model is used for learning the at least one of the undetermined parameter, the undetermined solving operator or the undetermined structural relationship in the iterative algorithm; and acquiring under-sampled K-space data to be processed, inputting the under-sampled K-space data into the magnetic-resonance imaging model, and generating a magnetic-resonance image.

Classes IPC  ?

• G01R 33/48 - Systèmes d'imagerie RMN
• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne
• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique

Abrégé

Disclosed are information transmission method, apparatus, device and medium for medical imaging application. The method includes: an imaging device corresponding to an application authorization request is determined according to the received application authorization request, and an application permission profile of the imaging device is acquired; and a medical imaging application corresponding to the imaging device is determined according to the application permission profile of the imaging device, and medical imaging application information corresponding to the medical imaging application is transmitted to the imaging device.

Classes IPC  ?

• G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p.ex. DICOM, HL7 ou PACS
• G16H 40/60 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santé; TIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux
• G06F 21/31 - Authentification de l’utilisateur
• G06F 3/12 - Sortie numérique vers une unité d'impression

Abrégé

A microfluidic system, including: a container, an ultrasound transmitter assembly, and a phononic crystal plate. The container is configured to accommodate a solution containing microparticles. The ultrasound transmitter assembly is configured to transmit ultrasonic waves to the phononic crystal plate, where the ultrasonic waves have a frequency which is the same as a resonance frequency of the phononic crystal plate. The phononic crystal plate is placed in the solution, and configured to generate a local acoustic field on a surface of the phononic crystal plate under excitation of the ultrasonic waves, and induce an acoustic microstreaming vortex to generate an acoustic streaming shear stress on the microparticles. The phononic crystal plate defines therein cavities, the respective cavities are arranged periodically in the phononic crystal plate, and all the respective cavities are filled with gas.

Classes IPC  ?

• B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes
• B06B 1/06 - Procédés ou appareils pour produire des vibrations mécaniques de fréquence infrasonore, sonore ou ultrasonore utilisant l'énergie électrique fonctionnant par effet piézo-électrique ou par électrostriction

Abrégé

The present invention provides a microelectrode, comprising a flexible layer, an electrically conductive layer and a plurality of platinum dendrite structures, wherein the electrically conductive layer is arranged in the flexible layer, and wherein on the surface of the flexible layer are a plurality of grooves within which the electrically conductive layer is revealed partially, and wherein each of the groove is provided with one platinum dendrite structure therein. The plurality of grooves serve as focal electrodes distributed uniformly, with smaller electrode sites and more recording points. The modified platinum dendrite structures increase the surface area, electrical performance, biocompatibility and service life of the microelectrode. Besides, creating virtual electrodes by current steering technique increases the number of stimuli received by microelectrode during use, and improves its resolution in applications.

Classes IPC  ?

• A61N 1/05 - Electrodes à implanter ou à introduire dans le corps, p.ex. électrode cardiaque
• H01B 1/02 - Conducteurs ou corps conducteurs caractérisés par les matériaux conducteurs utilisés; Emploi de matériaux spécifiés comme conducteurs composés principalement de métaux ou d'alliages

Abrégé

The present disclosure discloses a method and a system for generating a composite PET-CT image based on a non-attenuation-corrected PET image. The method includes: constructing a first generative adversarial network and a second generative adversarial network; obtaining a mapping relationship between a non-attenuation-corrected PET image and an attenuation-corrected PET image by training the first generative adversarial network; obtaining a mapping relationship between the attenuation-corrected PET image and a CT image by training the second generative adversarial network; and generating the composite PET-CT image by utilizing the obtained mapping relationships. According to the present disclosure, a high-quality PET-CT image can be directly composited from a non-attenuation-corrected PET image, and medical costs can be reduced for patients, and radiation doses applied to the patients in examination processes can be minimized.

Classes IPC  ?

• G06T 5/50 - Amélioration ou restauration d'image en utilisant plusieurs images, p.ex. moyenne, soustraction
• G06T 5/00 - Amélioration ou restauration d'image

Abrégé

The application provides a task scheduling simulation system, comprising a data preprocessing subsystem and a task scheduling subsystem. The data preprocessing subsystem filters the input cloud computing log information for abnormal data and extracts the running time of each task. The task scheduling subsystem enqueues or dequeues tasks from the batch task and real-time task running queues of each node, and keeps the tasks currently running in the cluster consistent with the actual production environment, and updates the number of CPU cores and the used and available memory capacity of each node according to resource requirement of each task. The mixed scheduling simulation of batch tasks and online tasks can be realized, and the resource simulation of the heterogeneous CPU core number and memory capacity of the cluster nodes can be simulated.

Classes IPC  ?

• G06F 9/48 - Lancement de programmes; Commutation de programmes, p.ex. par interruption
• G06F 30/20 - Optimisation, vérification ou simulation de l’objet conçu

Abrégé

The disclosure provides a low-dose image reconstruction method and system based on prior anatomical structure difference. The method includes: determining the weights of different parts in the low-dose image based on prior information of anatomical structure differences; constructing a generative network being taking the low-dose image as input extract features, and integrating the weights of the different parts in the feature extraction process, outputting a predicted image; constructing a determining network being taking the predicted image and standard-dose image as input, to distinguish the authenticity of the predicted image and standard-dose image as the first optimization goal, and identifying different parts of the predicted image as the second optimization goal, collaboratively training the generative network and the determining network to obtain the mapping relationship between the low-dose image and the standard-dose image; and reconstructing the low-dose image by using the obtained mapping relationship. The disclosure can obtain more accurate high-definition images.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• A61N 5/10 - Radiothérapie; Traitement aux rayons gamma; Traitement par irradiation de particules

Abrégé

The disclosure discloses a system for treating high-salt high-organic wastewater and recovering energy, the system includes a cold wall-type reactor (6), a multi-level cyclone separator (16, 19, and 25), a waste liquid feeding system, an oxidant feeding system and a fuel feeding system; The cold wall-type reactor designed by the disclosure is formed by inner and outer double-housing structures, a cooling medium is fed into a gap between the inner housing and the outer housing of the reactor, the fluid on an inner wall surface of the inner housing of the reactor is cooled below a supercritical temperature of the water by using countercurrent heat exchange, blockage of the inorganic salts is effectively prevented. The disclosure is capable of realizing gradient utilization of the reaction heat of the high-salt high-organic wastewater supercritical water oxidation system, and improving a system energy recovery utilization ratio in the greatest degree.

Classes IPC  ?

• C02F 11/08 - Oxydation par air humide
• C02F 1/38 - Traitement de l'eau, des eaux résiduaires ou des eaux d'égout par séparation centrifuge
• C02F 101/10 - Composés inorganiques
• C02F 101/12 - Halogènes ou composés halogénés
• C02F 101/16 - Composés de l'azote, p.ex. ammoniac
• C02F 101/30 - Composés organiques
• C02F 103/34 - Nature de l'eau, des eaux résiduaires ou des eaux ou boues d'égout à traiter provenant de l'industrie chimique non prévue dans les groupes

Abrégé

Provided are a method and device for magnetic resonance parameter imaging, medical equipment, and a storage medium. The method comprises: performing acceleration sampling with respect to an image to be reconstructed of an observation target in a preset parameter direction to acquire K-space data corresponding to the image to be reconstructed, calculating, on the basis of the K-space data and of a parameter relaxation model, a parameter value and a compensation coefficient of the image to be reconstructed, generating, on the basis of the compensation coefficient, a compensation image corresponding to the image to be reconstructed, calculating, on the basis of the compensation image, respectively a low-rank part and a sparse part of the image to be reconstructed so as to update the compensation image.

Classes IPC  ?

• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne
• G01R 33/561 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne par réduction du temps de balayage, c.à d. systèmes d'acquisition rapide, p.ex. utilisant des séquences d'impulsions écho-planar
• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique

Abrégé

A device for generating a droplet array, which comprises a substrate, a roller on the substrate, and a microgrooved chip on the outer surface of the roller, wherein a sealant is on a surface of the substrate close to the roller and the microgrooved chip comprises a chip body fitted to the roller and an array of microgrooves arranged on the chip body, the array of microgrooves consisting of a plurality of microgrooves arranged at intervals on the chip body. When the roller rolls, liquid between the substrate and the roller enters the microgrooves and forms droplets while the microgrooved chip detaches from the roller and combines with the sealant which seals the microgrooves, generating a droplet array. The device generates a droplet array having uniform droplet size, good repeatability. Further, the method is simple and highly efficient, and has broad application prospects in the fields of medicine and biology.

Classes IPC  ?

• B01L 3/02 - Burettes; Pipettes
• B01J 19/00 - Procédés chimiques, physiques ou physico-chimiques en général; Appareils appropriés

Abrégé

A parking lot data repair method and apparatus, a device, and a storage medium. The method comprises: calculating spatial similarity between two parking lots according to the spatial features of the parking lots and a spatial similarity measurement model; clustering the parking lots into different parking lot clusters according to the spatial similarity, and calculating a spatial similarity probability corresponding to each parking lot cluster; calculating data similarity between two sample parking lots in the same parking lot cluster, and according to the data similarity and the spatial similarity probability corresponding to the parking lot cluster, calculating the data similarity probability of the parking lot cluster under a similar spatial condition; and when the data similarity probability under the similar spatial condition exceeds a probability threshold value, performing data repair on the parking lot to be repaired in the parking lot cluster by means of a cyclic generation-type confrontation network.

Classes IPC  ?

• G08G 1/14 - Systèmes de commande du trafic pour véhicules routiers indiquant des places libres individuelles dans des parcs de stationnement
• G06F 16/75 - Groupement; Classement
• G06Q 50/30 - Transport; Communications
• G06G 1/14 - Dispositifs de calcul manipulés manuellement dans lesquels une ligne droite ou une ligne courbe doit joindre des points donnés sur une ou plusieurs échelles d'entrée à un ou plusieurs points sur une échelle de résultat
• G07B 15/02 - Dispositions ou appareils pour encaisser le prix des billets ou les droits d’entrée ou de péage en un ou plusieurs points de contrôle prenant en compte un facteur variable tel que la distance ou le temps, p.ex. pour le transport de passagers, les systèmes de parcs de stationnement ou les systèmes de location de véhicules

Abrégé

Provided are composite array electrode, preparation method thereof and use thereof. The composite array electrode comprises a microelectrode array substrate, and a modification layer formed on a surface of a microelectrode of the microelectrode array substrate, wherein the modification layer comprises a plurality of electrically conductive layers arranged at intervals on the surface of the microelectrode, an insulating layer arranged on the surface of the microelectrode except the electrically conductive layers, and wherein material for the electrically conductive layers comprises one or more of nano platinum, nano iridium, conductive polymer and carbon nanotubes. The composite array electrode effectively eliminates the influence of edge effect such that the electric field distributes uniformly on the microelectrode surface of the composite array electrode, significantly improving electrochemical performance and detection capability of the electrode.

Classes IPC  ?

• A61B 5/268 - Détection, mesure ou enregistrement de signaux bioélectriques ou biomagnétiques du corps ou de parties de celui-ci Électrodes bioélectriques à cet effet caractérisées par les matériaux des électrodes contenant des polymères conducteurs, p.ex. des polymères PEDOT:PSS
• C25D 7/12 - Semi-conducteurs
• A61B 5/1468 - Mesure des caractéristiques du sang in vivo, p.ex. de la concentration des gaz dans le sang, de la valeur du pH du sang en utilisant des procédés chimiques ou électrochimiques, p.ex. par des moyens polarographiques
• B08B 3/08 - Nettoyage impliquant le contact avec un liquide le liquide ayant un effet chimique ou dissolvant
• B08B 7/02 - Nettoyage par des procédés non prévus dans une seule autre sous-classe ou un seul groupe de la présente sous-classe par distorsion, battage ou vibration de la surface à nettoyer
• C25D 5/02 - Dépôt sur des surfaces déterminées
• C25D 5/34 - Prétraitement des surfaces métalliques à revêtir de métaux par voie électrolytique
• G01N 27/327 - Electrodes biochimiques
• A61N 1/05 - Electrodes à implanter ou à introduire dans le corps, p.ex. électrode cardiaque

Abrégé

A shimming system for magnetic resonance imaging is provided, which includes: a multi-channel local shim coil unit configured to be installed on an inspection table of a magnetic resonance imaging system, where the multi-channel local shim coil unit includes a local multi-channel shim coil and a radio frequency receiving coil for receiving magnetic resonance signals, and the radio frequency receiving coil is placed inside the local multi-channel shim coil and separated by a distance from the local multi-channel shim coil; a computer control system configured to install and set software controlled by a DC power and calculate field maps and calculate optimization processes; a DC power system communicatively connected to the computer control system to control a value of current of each channel; and a housing having a semi-cylindrical configuration, where the local multi-channel shim coil is only distributed on a semi-cylindrical surface of the semi-cylindrical configuration of the housing.

Classes IPC  ?

• G01R 33/3875 - Compensation des inhomogénéités utilisant des ensembles de bobines de correction, p.ex. compensation active
• G01R 33/44 - Dispositions ou appareils pour la mesure des grandeurs magnétiques faisant intervenir la résonance magnétique utilisant la résonance magnétique nucléaire [RMN]
• G01R 33/54 - Systèmes de traitement du signal, p.ex. utilisant des séquences d'impulsions
• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique
• G01R 33/48 - Systèmes d'imagerie RMN
• A61B 17/32 - Instruments chirurgicaux coupants
• G01R 33/24 - Dispositions ou appareils pour la mesure des grandeurs magnétiques faisant intervenir la résonance magnétique pour la mesure de la direction ou de l'intensité de champs magnétiques ou de flux magnétiques

Abrégé

The embodiments of the present disclosure are applicable to the technical field of computer science and application technology, and disclose a wireless body area network, a key generation method and a key distribution method in the wireless body area network, and a related device. The gait acceleration signal is extracted synchronously through the respective acceleration acquisition devices integrated with the coordinator and the wearable equipment, the position information corresponding to the peak value and the valley value in the gait acceleration signal is correspondingly extracted and is taken as the gait common information, and the gait common information is used to perform key distribution in the wireless body area network, the security and the consistency are higher, the calculation is simplified, the key distribution method is suitable for wearable devices having limited resources.

Classes IPC  ?

• H04M 1/66 - COMMUNICATIONS TÉLÉPHONIQUES Équipement de sous-station, p.ex. pour utilisation par l'abonné avec des moyens pour empêcher les appels non autorisés ou faux appels
• H04M 1/68 - Circuits pour empêcher l'écoute indiscrète
• H04M 3/16 - Centraux automatiques ou semi-automatiques avec disposition de verrouillage ou de secret dans les systèmes de lignes à postes groupés
• H04W 12/0431 - Distribution ou pré-distribution de clés; Mise en accord de clés
• H04W 4/80 - Services utilisant la communication de courte portée, p.ex. la communication en champ proche, l'identification par radiofréquence ou la communication à faible consommation d’énergie
• H04W 12/041 - Génération ou dérivation de clé
• H04L 9/08 - Répartition de clés
• H04W 12/037 - Protection de la confidentialité, p.ex. par chiffrement du plan de contrôle, p.ex. trafic de signalisation

Abrégé

A method for magnetic resonance imaging and plaque recognition includes: obtaining magnetic resonance undersampled K-space data; transforming the magnetic resonance undersampled K-space data to an image domain through inverse Fourier transform to obtain a preprocessed image; reconstructing the preprocessed image through a pre-established deep learning reconstruction model to obtain a high-resolution imaging image of a blood vessel wall; and recognizing plaques in the high-resolution imaging image of the blood vessel wall through a pre-established deep learning plaque recognition model. A neural network corresponding to the pre-established deep learning reconstruction model is a dense connection network. The magnetic resonance undersampled K-space data is head-and-neck combined magnetic resonance undersampled K-space data of the blood vessel wall.

Classes IPC  ?

• G06T 7/00 - Analyse d'image
• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique
• G06T 11/00 - Génération d'images bidimensionnelles [2D]
• A61B 5/02 - Mesure du pouls, du rythme cardiaque, de la pression sanguine ou du débit sanguin; Détermination combinée du pouls, du rythme cardiaque, de la pression sanguine; Evaluation d'un état cardio-vasculaire non prévue ailleurs, p.ex. utilisant la combinaison de techniques prévues dans le présent groupe et des techniques d'électrocardiographie; Sondes cardiaques pour mesurer la pression sanguine

Abrégé

A magnetic resonance imaging method includes: obtaining three-dimensional under-sampling data of a target object based on a first three-dimensional magnetic resonance imaging sequence; obtaining a three-dimensional point spread function based on the three-dimensional under-sampling data or a two-dimensional mapping data of the target object; obtaining a sensitivity map of the target object based on the data collected by three-dimensional low-resolution complete sampling; performing imaging reconstruction to the three-dimensional under-sampling data based on the three-dimensional point spread function and the sensitivity map to obtain a reconstructed magnetic resonance image. The first three-dimensional magnetic resonance imaging sequence has a first sinusoidal gradient field on a phase direction and a second sinusoidal gradient field on a layer selection direction. 0-order moments of the first and the second three-dimensional magnetic resonance imaging sequences are 0. A phase difference between the first and the second three-dimensional magnetic resonance imaging sequence is π/2.

Classes IPC  ?

• A61B 5/055 - Détection, mesure ou enregistrement pour établir un diagnostic au moyen de courants électriques ou de champs magnétiques; Mesure utilisant des micro-ondes ou des ondes radio faisant intervenir la résonance magnétique nucléaire [RMN] ou électronique [RME], p.ex. formation d'images par résonance magnétique
• G01R 33/28 - Dispositions ou appareils pour la mesure des grandeurs magnétiques faisant intervenir la résonance magnétique - Détails des appareils prévus dans les groupes
• G01R 33/48 - Systèmes d'imagerie RMN

Abrégé

The present disclosure relates to an enhanced generative adversarial network and a target sample recognition method. The enhanced generative adversarial network in the present disclosure includes at least one enhanced generator and at least one enhanced discriminator, where the enhanced generator obtains generated data by processing initial data, and provides the generated data to the enhanced discriminator; the enhanced discriminator processes the generated data and feeds back a classification result to the enhanced generator; the enhanced discriminator includes: a convolution layer, a basic capsule layer, a convolution capsule layer, and a classification capsule layer, and the convolution layer, the basic capsule layer, the convolution capsule layer, and the classification capsule layer are sequentially connected to each other.

Classes IPC  ?

• G06N 3/08 - Méthodes d'apprentissage
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques

Abrégé

2) for use as photodynamic therapy (PDT) agent. The combination of rhodamine organic dye and luminescent transition metal centers in such hybrid systems exhibits the synergistic merits, including low dark cytotoxicity, selective tumor cell uptake, high molar absorptivity for low-energy excitation in the visible region, and high photostability.

Classes IPC  ?

• C07F 15/00 - Composés contenant des éléments des groupes 8, 9, 10 ou 18 de la classification périodique
• C07F 13/00 - Composés contenant des éléments des groupes 7 ou 17 de la classification périodique
• A61P 35/00 - Agents anticancéreux

Abrégé

The present disclosure relates to a 1D partial Fourier parallel magnetic resonance imaging method with a deep convolutional network and belongs to the technical field of magnetic resonance imaging. The method includes steps of: creating a sample set and a sample label set for training; constructing an initial deep convolutional network model; inputting a training sample of the sample set to the initial deep convolutional network model for forward process, comparing an output result of the forward process with an expected result in the sample label set, and performing training with a gradient descent method until a parameter of each layer which enables consistency between the output result and the expected result to be maximum is obtained; creating an optimal deep convolutional network model by using the obtained parameter of the each layer; and inputting a multi-coil undersampled image sampled online to the optimal deep convolutional network model, performing the forward process on the optimal deep convolutional network model, and outputting a reconstructed single-channel full-sampled image. The present disclosure can well remove the noise of the reconstructed image, reconstruct a magnetic resonance image with a better visual effect, and has high practical value.

Classes IPC  ?

• G01R 33/561 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne par réduction du temps de balayage, c.à d. systèmes d'acquisition rapide, p.ex. utilisant des séquences d'impulsions écho-planar
• G01R 33/00 - Dispositions ou appareils pour la mesure des grandeurs magnétiques
• G06N 3/08 - Méthodes d'apprentissage

Abrégé

Provided are a microfluidic apparatus, a method and system for introducing a substance into a cell. The microfluidic apparatus includes a cavity channel, a bulk wave generating device and a surface acoustic wave generating device; a microstructure is arranged on an inner wall of the cavity channel, and the microstructure is constructed for forming a bubble by a solution at the microstructure when the solution is injected into the cavity channel; the bulk wave generating device is configured to generate a bulk wave, the bulk wave enables the bubble to resonate for generating a flow field; and the surface acoustic wave generating device is configured to generate a surface acoustic wave and control a position of at least one particle in the solution.

Classes IPC  ?

• B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes
• C12N 15/89 - Introduction de matériel génétique étranger utilisant des procédés non prévus ailleurs, p.ex. co-transformation utilisant la micro-injection

Abrégé

A visual continuous spatial directed evolution method is disclosed. The host grows and moves in a solid culture space, the host carrying a foreign target gene to be evolved and containing a gene element that assists the evolution of the target gene, the target gene being correlated with the growth and movement of the host. Depending on different spatial distribution patterns formed in the solid culture space during the growth and movement of the host, screening is performed to obtain an evolved product. This method is carried out directly in the solid culture space. Depending on images of different spatial distribution morphologies visible to the naked eye that are locally formed, selection of evolved products is performed without the need for liquid fed-batch culture equipment. In addition, the evolution effect is visually observed through the infection spots formed during evolution, so that no real-time monitoring equipment is required.

Classes IPC  ?

• C40B 30/06 - Procédés de criblage des bibliothèques en mesurant les effets sur des cellules, des tissus ou des organismes vivants
• C12N 7/00 - Virus, p.ex. bactériophages; Compositions les contenant; Leur préparation ou purification
• C12N 15/10 - Procédés pour l'isolement, la préparation ou la purification d'ADN ou d'ARN
• C12N 15/70 - Vecteurs ou systèmes d'expression spécialement adaptés à E. coli
• C12N 15/85 - Vecteurs ou systèmes d'expression spécialement adaptés aux hôtes eucaryotes pour cellules animales
• C40B 50/06 - Procédés biochimiques, p.ex. utilisant des enzymes ou des micro-organismes viables entiers
• C40B 60/08 - Appareils intégrés spécialement adaptés à la fois à la création et au criblage de bibliothèques

Abrégé

A three-degree-of-freedom parallel mechanism, includes a fixed platform, a movable platform, and three kinematic chains, where at least one of the three kinematic chains is a flexible chain; and the flexible chain includes a first connecting rod, a second connecting rod, and an axis-variable revolute pair, the axis-variable revolute pair includes a fixed member, a movable member, and a spherical pair, one end of the fixed member is fastened on the fixed platform, the other end of the fixed member fits and abuts against an inclined surface of the movable member, the spherical pair is accommodated in the fixed member, a spherical hinge connecting rod of the spherical pair penetrates the movable member, the first connecting rod is rotatably connected to the spherical hinge connecting rod and the second connecting rod, and the second connecting rod is spherically hinged to the movable platform.

Classes IPC  ?

• B25J 9/00 - Manipulateurs à commande programmée
• F16C 7/02 - Structure des bielles de longueur fixe

Abrégé

A microfluidic chip (100), an apparatus, a system, and a control and preparation method therefor. The method comprises: a substrate (101), and an electrode layer (102) and a functional layer (103) sequentially formed on the substrate (101), said electrode layer (102) comprising a plurality of electrode groups (1021) arranged in an array, the electrode groups (1021) being used for converting electrical signals into acoustic signals when an electrode group is activated, and transmitting the acoustic signals to the functional layer (103); and the functional layer (103) being used for carrying a sample to be tested, and for absorbing the acoustic wave signals emitted by the activated electrode group (1021) and converting same into thermal energy for heating the sample to be tested that is carried at the position corresponding to the activated electrode group (1021).

Classes IPC  ?

• B01L 3/00 - Récipients ou ustensiles pour laboratoires, p.ex. verrerie de laboratoire; Compte-gouttes

Abrégé

A method of processing plaques in magnetic resonance imaging of vessel wall include: step S101, training a generative adversarial network and a capsule neural network to obtain a trained generator network and a trained capsule neural network; and step S102, cascade-connecting the trained generator network with the capsule neural network into a system to recognize and classify plaques in magnetic resonance imaging of vessel wall. In one aspect, the capsule neural network has more abundant vascular plaques characteristic information represented by vector; in another aspect, when the trained generator network and the capsule neural network are cascaded into the system to recognize and classify the plaques in magnetic resonance imaging of vessel wall, an accuracy of recognition and classification may be greatly improved. A device for processing the method as well as a computer for implementing are also disclosed.

Classes IPC  ?

• G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
• G06T 7/00 - Analyse d'image
• G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p.ex. l’édition
• G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
• G06N 3/08 - Méthodes d'apprentissage
• G06T 11/00 - Génération d'images bidimensionnelles [2D]

Abrégé

i and the function relation. The method can eliminate the impact of concentration and does not require any estimation or measurement of the parameters such as the concentration of exchangeable protons, the longitudinal relaxation time of water, etc., and therefore can measure pH more accurately, conveniently and non-invasively.

Classes IPC  ?

• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne

Abrégé

The present disclosure provides an atrial fibrillation signal recognition method, apparatus and device. The method comprises: obtaining an electrocardiogram signal to be recognized; inputting the electrocardiogram signal to be recognized to a pre-established atrial fibrillation signal recognition model, and outputting an atrial fibrillation signal recognition result, where the atrial fibrillation signal recognition model is established in the following way: obtaining a specified number of electrocardiogram sample signals and corresponding identifier information; balancing, according to the number of normal signals, atrial fibrillation signals by means of SMOTE; establishing a network structure of multiple convolutional neural networks, each of the convolutional neural networks being provided with a specific receptive field for recognizing the atrial fibrillation signals of a corresponding granularity; and inputting the normal signals and the balanced atrial fibrillation signals to the network structure for training to generate an atrial fibrillation signal recognition model.

Classes IPC  ?

• G06N 3/00 - Agencements informatiques fondés sur des modèles biologiques
• G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicales; TIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p.ex. basé sur des systèmes experts médicaux
• A61B 5/00 - Mesure servant à établir un diagnostic ; Identification des individus
• G06N 3/04 - Architecture, p.ex. topologie d'interconnexion
• G06N 3/08 - Méthodes d'apprentissage
• A61B 5/352 - Détection des crêtes de l'onde R, p.ex. pour la synchronisation d'appareils de diagnostic; Estimation de l’intervalle entre crêtes R
• A61B 5/361 - Détection de la fibrillation

Abrégé

A planar lens (100) and a manufacturing method for a planar lens (100) relate to the technical field of lenses, the planar lens (100) being a focusing lens and comprising an acoustic soft material tangible structure (110) and a cover layer (120), the acoustic soft material tangible structure (110) comprises a plurality of combination lenses (130) located in the same plane, each combination lens (130) comprises a circular part (131) and a plurality of concentric annular parts (132) which are continuously arranged around the circular part (131), the thicknesses of each two adjacent annular parts (132) in each combination lens (130) are different, and the thickness of each annular part (132) is related to the focal length of the respective combination lens (130); and the cover layer (120) covers the outer surface of the acoustic soft material tangible structure (110) to form the planar lens (100).

Classes IPC  ?

• G02B 3/00 - Lentilles simples ou composées
• G10K 11/30 - Procédés ou dispositifs pour transmettre, conduire ou diriger le son pour focaliser ou pour diriger le son, p.ex. balayage utilisant la réfraction, p.ex. lentilles acoustiques

Abrégé

A dual-nuclear radio frequency (RF) coil device includes a first RF coil and a second RF coil. The first RF coil includes at least one adjustment capacitor, the first RF coil is configured to generate a first magnetic field, and a direction of a primary magnetic field of the first magnetic field is a first direction. The second RF coil includes an electric dipole and a tuning and matching circuit connected between two conductors of the electric dipole. The second RF coil is configured to generate a second magnetic field and a direction of a primary magnetic field of the second magnetic field is a second direction; the electric dipole is disposed in a center line of the first RF coil and an insulating layer is disposed between the electric dipole and the first RF coil; and the first direction is perpendicular to the second direction.

Classes IPC  ?

• G01R 33/34 - Systèmes d'excitation ou de détection, p.ex. utilisant des signaux radiofréquence - Détails de structure, p.ex. résonateurs
• G01R 33/36 - Systèmes d'excitation ou de détection, p.ex. utilisant des signaux radiofréquence - Détails électriques, p.ex. adaptations ou couplage de la bobine au récepteur

Abrégé

2,1. In this manner, calibration is not required while information sparsity is developed. Moreover, the method is robust.

Classes IPC  ?

• G01R 33/561 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne par réduction du temps de balayage, c.à d. systèmes d'acquisition rapide, p.ex. utilisant des séquences d'impulsions écho-planar
• G01R 33/56 - Amélioration ou correction de l'image, p.ex. par des techniques de soustraction ou d'établissement de moyenne
• G06T 11/00 - Génération d'images bidimensionnelles [2D]

Abrégé

A method, an apparatus, a device, and a storage medium for extracting a cardiovascular vessel from a CTA image, the method including the steps of: performing erosion operation and dilation operation on image data successively via a preset structural element to obtain a structure mask; performing a slice-by-slice transformation on the plane of section images of the structural mask to acquire the first ascending aortic structure in the structural mask, and acquiring an aortic center position and an aortic radius in the last slice of the plane of section image of the said structural mask; establishing a binarized sphere structure according to the aortic center position and the aortic radius, and synthesizing a second ascending aorta structure by combining the first ascending aorta structure with the structure mask and the binarized sphere structure.

Classes IPC  ?

• G06T 7/11 - Découpage basé sur les zones
• G06T 5/30 - Erosion ou dilatation, p.ex. amincissement
• G06T 7/00 - Analyse d'image
• G06V 10/34 - Lissage ou élagage de la forme; Opérations morphologiques; Squelettisation
• G06T 7/262 - Analyse du mouvement utilisant des procédés de transformation de domaine, p.ex. des procédés de transformée de Fourier

Abrégé

A method and a device for acquiring biomechanical parameters based on an ultrasonic elastomyogram are provided, wherein the method includes: synchronously collecting a dynamic myodynamics image sequence and a dynamic elasticity image sequence of a single skeletal muscle under continuous stretching; acquiring a myodynamics parameter corresponding to each myodynamics image in the dynamic myodynamics image sequence and an elasticity modulus value corresponding to each elasticity image in the dynamic elasticity image sequence respectively; and generating an ultrasonic elastomyogram curve with the myodynamics parameter as the abscissa and the synchronized elasticity modulus value as the ordinate, and estimating a muscle biomechanical parameter based on the ultrasonic elastomyogram curve. Dynamically changing biomechanical parameters can be obtained, and the obtained muscle biomechanical parameters have relatively high accuracy.

Classes IPC  ?

• A61B 8/08 - Détection de mouvements ou de changements organiques, p.ex. tumeurs, kystes, gonflements

Abrégé

Disclosed is a three-branched six-degree-of-freedom parallel mechanism with curved sliding pairs, which includes a base, a moving platform, and three identical kinetic branches. The kinetic branches are radially and evenly distributed and arranged between the base and the moving platform. Each kinetic branch includes a first curved link assembly, a first motor, and a support link. One end of the support link is hinged to the moving platform. One end of the first curved link assembly is hinged to the support link. The first motor is disposed on the base and is configured for driving the first curved link assembly to rotate, where an arc length of the first curved link assembly is changed as the first curved link assembly is driven to rotate.

Classes IPC  ?

• G05G 11/00 - Mécanismes de commande manuelle équipés de plusieurs organes de commande travaillant avec un seul organe commandé
• B25J 9/00 - Manipulateurs à commande programmée
• B25J 9/08 - Manipulateurs à commande programmée caractérisés par des éléments de construction modulaires

Abrégé

A method and an apparatus for extracting a centerline of a tubular object are provided. The method includes: preprocessing an image of the tubular object whose centerline is to be extracted to obtain an enhanced image, acquiring a gradient vector flow field of the enhanced image; acquiring a deformation force parameter based on the gradient vector flow field and extracting ridge points of the tubular object from the enhanced image, establishing a regularized open curve deformable model; if a deformation end condition is not met, deforming and processing one ridge line segment in the initial ridge line segment list based on the model to obtain a centerline segment of the tubular object, updating the initial ridge line segment list based on the ridge line segment traversed; if the deformation end condition is met, generating a centerline of the tubular object based on the centerline segments.

Classes IPC  ?

• G06T 7/66 - Analyse des attributs géométriques des moments d'image ou du centre de gravité
• G06T 7/12 - Découpage basé sur les bords
• G06T 7/269 - Analyse du mouvement utilisant des procédés basé sur le gradient
• G06T 7/149 - Découpage; Détection de bords impliquant des modèles déformables, p.ex. des modèles de contours actifs