Panovision IP

Embodiments of the present disclosure provide a medical agent generation system, a medical system, and a medical agent generation method. The system includes an agent platform. The agent platform is deployed on a cloud platform. The agent platform is configured to generate and/or edit a medical agent based on input information of a user. The medical agent is exported to a medical system for execution, and/or the medical agent is imported from the medical system for editing.

A method for medical scanning is provided. The method includes: obtaining, via a user terminal, an input of a user specifying scan requirements with respect to a target subject to be scanned; extracting, from the input, scan requirement information; obtaining medical record information of the target subject; and generating a scanning scheme for the target subject by processing the scan requirement information and the medical record information, wherein the processing of the scan requirement information and the medical record information is performed with reference to long-term memory information stored in the at least one storage device, and the long-term memory information comprises at least one of a rule database, a knowledge graph, or a historical scanning scheme database.

Disclosed is a method for image processing. The method includes: obtaining one or more image sequences, each of the one or more image sequences including one or more images; determining key information of at least a portion of the one or more images in each of the one or more image sequences; and processing the one or more image sequences based on feature information of each of the one or more image sequences, the feature information of each of the one or more image sequences including the key information of the at least a portion of the one or more images in the image sequence.

A system for generating a 3D heart model based on 2D ultrasound image is provided. The system includes at least one storage device and at least one processor configured to communicate with the at least one storage device. The at least one storage device includes a set of instructions. The at least one processor is configured to communicate with the at least one storage device. When executing the set of instructions, the at least one processor is configured to direct the system to perform operations. The operations includes: obtaining a 2D ultrasound image of a subject; obtaining a target 3D model of an anatomical structure of the subject; obtaining a transformed target 3D model by transforming the target 3D model to align the target 3D model with the 2D ultrasound image; and generating a target 3D image of the subject based on the transformed target 3D model and the 2D ultrasound image.

The present disclosure relates to systems and methods for positioning a region of interest (ROI). The methods may include obtaining an image of an object captured by an imaging device. The methods may extracting image information of the image. The methods may obtaining feature information of a region of interest (ROI) in the object. The methods may determining position information of the ROI in the image using a positioning model based on the image information of the image and the feature information of the ROI.

The present disclosure mainly relates to a nonlinear resistance strain sensor. The nonlinear resistance strain sensor includes an elastic substrate and a plurality of conductive substances. The plurality of conductive substances are uniformly distributed on the elastic substrate. When the elastic substrate is pulled, the length thereof correspondingly increases, and the density of the plurality of conductive substances on the elastic substrate decreases, thereby changing the overall resistance thereof. In the above manner, the nonlinear resistance strain sensor of the present disclosure has nonlinear and high-sensitivity resistance strain performance.

Embodiments of the present disclosure provide a magnetic resonance imaging (MRI) method, an MRI device, and an anti-interference device. The MRI method is implemented by the MRI device, and the MRI method includes: adjusting an operating frequency of at least one electronic device located inside a scanning room or entering into the scanning room, an adjusted frequency of the electronic device is outside an operating frequency of a magnetic resonance imaging device.

The present disclosure provides a system and method for scanning a subject. The method includes determining reference dimensions, along the width direction of the table, of the subject on the table at positions along the moving direction of the table; dividing, based on the reference dimensions, the subject into at least one region along the moving direction of the table, the at least one region including at least one of a first region or a second region; and controlling a relative motion between the detector and the table to perform scanning on the at least one region in sequence along the moving direction of the table. During scanning one of the at least one region, the detector moves along the width direction of the table relative to the table.

Embodiments of the present disclosure provide a sitting posture detection method and apparatus based on UWB, a device and a storage medium, which are applied in the technical field of intelligent analysis. The method comprises steps of: by a UWB signal receiver, receiving and amplifying a pulse signal to obtain a first pulse signal, adjusting the phase of the first pulse signal of a corresponding frame based on the difference between the average phase of a reference pulse signal and the phase of the reference pulse signal of any frame, and using a cascade filter to remove noise and increase the signal-to-noise ratio of the received baseband signal to obtain a second pulse signal; using a sudden change in the amplitude of the second pulse signal and/or Doppler information as a sign of a sitting posture change, and determining target distance and angle information of different sitting postures; and, splicing the target distance and angle information as a joint feature and inputting the joint feature into an SVM classifier to obtain a result of sitting posture detection. In this way, the accurate location of a target object can be accurately tracked, and the sitting posture of an individual can be monitored in real time without involving the user's privacy.

A measurement system for personalized bone and articular cartilage morphology comprises a database, an image capture module, an image analysis module, a neural network model, a model building module, and a novel computation module. The database is configured to store a dataset. The image capture module is configured to capture a plurality of skeletal images of a subject. The image analysis module is configured to obtain skeletal and cartilage shape parameters through statistical shape modeling and principal component analysis and generate 3D models of the skeleton and cartilage. The neural network model is configured to generate and output skeletal motion parameters based on the input skeletal and cartilage shape parameters. The model building module is configured to generate a personalized joint skeleton and cartilage model based on the 3D models of the skeleton and cartilage and the skeletal motion parameters. The novel computation module is configured to simulate the relative positions of the first bone and cartilage 3D model and the second bone and cartilage 3D model of the subject during exercise based on the personalized joint skeleton and cartilage model, and to calculate an actual cartilage shape and the cartilage wear value of the subject by eliminating overlapping cartilage regions in the first bone and cartilage 3D model and the second bone and cartilage 3D model during exercise.