13552 results about "Medical physics" patented technology

Various wearable health monitoring devices are described herein. Some implementations include a housing including a front side and a back side configured to face tissue of the wearer when the device is worn; and a sensor assembly positioned by the back side of the housing. The sensor assembly can include emitters and detectors positioned on a surface of a substrate and a frame positioned adjacent to the surface of the substrate and configured to inhibit transmission of optical radiation through the frame. The frame can comprise an emitter chamber housing the emitters; and one or more detector chambers housing the one or more detectors.

A wearable system can include an electronic device configured to measure one or more physiological parameters of a patient and a wearable device configured to operably position the electronic device. The electronic device can have at least one light emitter and at least one light detector and be configured to measure at least a pulse oximetry measurement. The wearable device can have a main body with a cavity configured to position the electronic device, a securement portion connected to the main body and configured to secure the main body to the patient, and storage component configured to store patient identification data associated with the patient. When the electronic device and the wearable device are secured to one another, the patient identification data can be transferred from the wearable device to the electronic device.

The invention discloses a multi-source heterogeneous medical data fusion and intelligent diagnosis method, and relates to the technical field of medical data processing and intelligent diagnosis, and the method comprises the specific steps: firstly, synchronously collecting medical images and clinical text data of a patient, and carrying out the correlation and integration to form a heterogeneous diagnosis data set; performing standardized feature extraction to obtain a feature set in a unified format; then constructing a parallel model, fusing features by using a cross-modal attention alignment technology, and guiding correction by means of a knowledge graph; and finally, the cross-modal diagnosis features are input into the reference model, automatic focus positioning is realized through processing, and a visual marker graph is output. Heterogeneous data of medical images and clinical texts are synchronously integrated, and the diagnosis feature reliability is improved through standardization processing, feature fusion and the like; a focus sensing mask is generated through comparison with a normal model, a multi-scale feature fusion technology is combined to realize automatic and accurate positioning of the focus, a large amount of labeled data is not needed, the process is simplified, and the diagnosis efficiency and accuracy are improved.

The invention discloses a renal clear cell carcinoma prognosis prediction method based on multi-mode MRI (Magnetic Resonance Imaging) image and digital pathological omics fusion. The method comprises the following steps: S1, collecting a training data set based on an MR image and a pathological image; s2, feature extraction of MR radiomics; s3, deep learning feature extraction of the pathological image; s4, an MR-pathological feature fusion module; and S5, deploying the network. According to the method, depth features with prognosis information are obtained from two scales of pre-treatment images and post-operation pathology, effective features are extracted by adopting image omics and a convolutional neural network mode according to data characteristics of MR images and pathology images, and depth fusion of the two types of features is completed in a hidden space through a multi-task guiding mode, so that the accuracy of the MR image and the pathology image is improved. A precise prognosis model with multi-scale information is provided, and the method has a relatively strong clinical application prospect and is of great significance for realizing precise immunotherapy and improving prognosis of a patient.

Embodiments of the present invention provide a therapeutic device. The therapeutic device includes an inner layer including a plurality of sensing locations and a plurality of stimulating locations constructed therewithin. Furthermore, the therapeutic device includes a plurality of stimulation elements located within the plurality of stimulating locations. The therapeutic device further includes a plurality of optical fibers including a plurality of respective first optical endpoints and a plurality of respective second optical endpoints, the plurality of first optical endpoints located within the plurality of sensing locations. Furthermore, the therapeutic device includes an optical sensor configured to receive electromagnetic radiation from the plurality of second optical endpoints. The therapeutic device also includes a control module configured to determine radiation characteristics of the electromagnetic radiation received by the optical sensor and activate one or more of the plurality of stimulation elements in correlation with the determined radiation characteristics.

Disclosed are approaches to data acquisition, analysis, and computational forecasting that employs quantitative MRI data to predict the response of cancer to therapy. Example protocols detail how to acquire needed images followed by registration, segmentation, quantitative perfusion and diffusion analysis, model calibration, and prediction. The response of individual cancer patients to therapy is forecast by application of a biophysical, reaction-diffusion model to these data. Application of the protocol results in coregistered MRI data from at least two scan visits that quantifies an individual tumor's size, cellularity and vascular properties. This enables a spatially resolved prediction of how a particular patient's tumor will respond to therapy. A modified therapy can be determined based on predicted response.

Systems and subsystems for closing an end effector of a stapler are disclosed. More specifically, the present disclosure relates to systems, devices, and subsystems for attachments for robotic surgeries. The surgical instrument is a robotic attachment. The surgical instrument includes a closure subsystem that moves independently of other subsystems that are operable independently of each other.

The embodiment of the invention discloses a spinal metastatic tumor treatment scheme generation system. According to one specific embodiment, the system comprises a data processing server, an information fusion server and a scheme generation server which are in communication connection with one another, and the data processing server is used for preprocessing multi-source patient data to obtain standard multi-source patient data; the information fusion server is used for executing the following steps: performing feature code fusion on standard multi-source patient data to obtain a multi-source patient feature vector; performing feature enhancement on the multi-source patient feature vector to obtain a joint patient characterization vector; generating an initial therapeutic schedule result based on the joint patient characterization vector; and the scheme generation server is used for performing feature decision processing on the initial treatment scheme result to obtain a final treatment report. According to the embodiment, waste of computing resources can be reduced, and system response time can be shortened.

The invention discloses a breast ultrasound image processing method and device, a terminal, a storage medium and a computer program product, and the method comprises the steps: carrying out the data preprocessing of a breast ultrasound image sub-data set, obtaining a breast ultrasound image sample, and dividing the breast ultrasound image sample into a training set and a test set; the method comprises the following steps: constructing a segmentation network model by fusing an OfficientViT encoder, a symmetric U-Net decoder and a CBAM attention enhancement module, and designing a joint loss function; based on the joint loss function, training the segmentation network model by using the training set to obtain a segmentation network training model; and testing the segmentation network training model by using the test set, and optimizing the segmentation network training model according to a test result to obtain a breast tumor region segmentation model. According to the scheme, the breast tumor region segmentation model is set by fusing the codec, the CBAM attention enhancement module and the joint loss function, and the breast tumor region can be accurately segmented from the breast ultrasound image.

This disclosure relates to systems, methods, and devices for plaque analysis, vessel and fluid flow analysis, and / or risk determination or prediction thereof. Some embodiments relate to determining fractional flow reserve (FFR) values. Some embodiments relate to determining FFR values using 3D-printed models. Some embodiments relate to identifying thin cap fibroatheroma based on analysis of computed tomography (CT) imaging. Some embodiments relate adjusting calcified plaque thresholds for CT images to address effects of calcium blooming.

The present disclosure involves a medical device. The medical device includes an elongate cable assembly having a distal connector, a proximal connector, and a cable body coupling the proximal and distal connectors. The distal connector is configured for coupling with a diagnostic medical device. The proximal connector is configured for coupling with a medical measurement system. An electronic component is located inside the distal connector or the associated cable housing. The electronic component includes an analog-to-digital converter (ADC) and a microprocessor. The ADC is configured to receive medical data gathered by the diagnostic medical device and convert the medical data into digital signals. The microprocessor is coupled to an output of the ADC and configured to process the digital signals into a format that is readable by the medical measurement system.

The invention relates to the field of man-machine interaction, and particularly discloses a multi-mode man-machine interaction application system for sky-eye insight based on a pathologist visual angle, which is characterized in that firstly, a candidate focus thermodynamic diagram is generated through rapid scanning of a full-slice image, low-power lens global browsing of a doctor is simulated, and the doctor is guided to lock a key area interactively through professional judgment; therefore, the processing efficiency of the oversized image is greatly improved. And then, the system only performs high-resolution deep analysis on the focus confirmed by the doctor, and performs multi-modal fusion on the extracted microscopic visual features and the patient text information to generate a preliminary report with an interpretable basis, so that the problem that the multi-modal function deviates from a clinical core task is solved. Finally, the doctor can check and finalize the report through visual interaction, and the dominant position and the final decision making right of the doctor in the diagnosis process are ensured, so that the bottlenecks of black box operation and low clinical acceptability of a traditional AI system are overcome.

The invention belongs to the technical field of radiotherapy dose simulation measurement, and provides a heavy ion fixed machine head radiotherapy dose simulation measurement method and system. The method comprises the following steps: firstly, in a solid water model, according to a layering and key area encryption sampling principle, carrying out finite point and / or cutting layer dose measurement to obtain sparse dose data and a sampling position; inputting the three-dimensional dose distribution and a sampling position mask into a coding-decoding structure and a mask perception neural network with an attention mechanism in a decoding stage, and outputting complete three-dimensional dose distribution; and finally, outputting a simulation result containing dose distribution and uncertainty distribution. The method improves dose reconstruction precision and clinical quality control efficiency, and is suitable for dose verification before heavy ion radiotherapy.

The invention discloses a method and a device for detecting internal defects of a special pipeline with a rifling. The device for detecting the internal defects of the special pipeline with the rifling comprises a detection equipment walking mechanism, the CCD industrial camera is used for collecting core images, and the CCD industrial camera is arranged at the foremost end of the special pipeline internal defect detection device with the rifling; the CCD industrial camera is connected to the holder, and the holder can rotate in all directions; the light supplementing light source can adjust the intensity of the light source and is used for adjusting the intensity of the light source and improving the imaging effect; the ultrasonic detection module comprises an ultrasonic probe and is used for identifying internal defects of the pipeline; the internal defect detection device for the special pipeline with the rifling further comprises a positioning device, a data processing terminal and a data transmission line. According to the invention, the problems of difficult carrier advancing stability, insufficient detection coverage and data fusion, and limited defect quantification and positioning precision in the prior art can be solved.

A computer system that performs quality control (QC) on images associated with diffusion and structural magnetic resonance imaging (MRI) is described. This computer may include: a computation device that executes program instructions; and memory that stores the program instructions. During operation, the computer system may automatically perform a set of validation operations, where, when one or more of the validation operations fails, the images are rejected. Moreover, the set of validation operations may include: performing QC on brain-tissue segmentation; performing QC on diffusion MRI processing; and performing QC on bundles determined from the images using a tractometry technique.

The invention discloses a method and system for evaluating infusion operation of intern medical staff, and belongs to the field of infusion, and the method comprises the steps that the operation of the intern medical staff is collected in multiple modes, and the multiple modes comprise a visual mode, a touch mode and a physiological signal mode; inputting the collected operation of the intern medical staff into the multi-modal infusion evaluation model, performing feature extraction by the multi-modal infusion evaluation model in a modal manner, and performing cross-modal attention fusion on feature vectors of different modals; and finally, comparing the calculated total feature tensor Hfusion with a standard total feature tensor Hfusion ', and outputting a final score of the practice medical personnel according to a preset scoring standard. According to the scheme, multi-dimensional data such as visual, tactile and physiological signals are synchronously collected through a multi-modal fusion method, operation details are comprehensively covered, comprehensive evaluation is carried out, and evaluation objectivity is improved.

The invention relates to the technical field of computer vision, image recognition and intelligent medicine management, in particular to a medicine bottle label content recognition method based on multiple cameras and YOLOv8. The method at least comprises the following steps: S1, deploying a medicine bottle label generation system, and generating a label; s2, multi-camera image acquisition and preprocessing; s3, carrying out chessboard calibration and space positioning; s4, medicine bottle label detection and label character recognition and structured analysis; and S5, system integration and application. According to the invention, through combination of multi-camera and multi-angle acquisition and checkerboard calibration positioning and combination with YOLOv8 label detection and OCR identification, high precision, high efficiency, end-to-end automation and system integration of medicine bottle label identification are realized, the defects of precision, efficiency, environmental adaptability and management integration in the prior art are overcome, and the system is suitable for popularization and application. The method has obvious technical advantages and practical value.

The invention discloses a 3DGS-based integrated visual angle synthesis and sparse visual angle CT reconstruction method, which comprises the following steps: establishing an internal and external parameter matrix through X-ray scanning parameters, constructing an initial voxel space and an initialized 3DGS radiation field by combining sparse visual angle projection data and based on an ACUI strategy, modeling anisotropic radiation intensity by utilizing a radiation intensity response function, and reconstructing a 3D visual angle CT model. And generating a virtual projection by adopting volume consistency rendering. And the optimized radiation field is converted into a voxel grid, density contribution is applied to carry out voxel space reconstruction, a reconstructed voxel space is obtained, and a new 3DGS radiation field is generated. And re-rendering the virtual visual angle projection based on the new 3DGS radiation field, performing iterative optimization by using a loss function, and outputting a new visual angle synthetic image and a CT reconstruction body until a preset number of iterations is reached. And an efficient process of one-time training and dual output is realized. The efficiency and precision of X-ray imaging are improved, the radiation dose of a patient is reduced, and meanwhile, a higher-quality imaging solution is provided for medical diagnosis.

The invention discloses an intelligent pulmonary tuberculosis recognition method and system based on image data, and relates to the technical field of image recognition, and the method comprises the steps: collecting and preprocessing conventional inspection data from different medical devices, and forming a standardized data set; extracting features from the standardized data set by using a deep learning model, and positioning a suspected focus area; based on the positioned suspected focus area, constructing a personalized risk assessment model, and generating a risk score; performing focus quantitative analysis based on the risk score, and generating a diagnosis report; the diagnosis report is applied to clinical practice, and a personalized diagnosis and treatment plan is made; according to the method, the personalized risk assessment model is constructed based on the positioned suspected focus area, the risk score is generated, and quantitative assessment of the health condition of the patient is realized.

The subject matter described in this disclosure can be embodied in methods, systems, and program products for receiving user input that selects an arrangement of surgical instrument trays for use during a surgical procedure. A display device presents a graphical representation of the selected arrangement of surgical instrument trays. A computing system receives image data depicting multiple actual surgical instrument trays; and analyzes the image data to determine an extent to which the multiple actual surgical instrument trays and actual surgical instruments located on the trays match the selected arrangement of surgical instrument trays. The display device presents a graphical indication of the extent to which the multiple actual surgical instrument trays match the selected arrangement of surgical instrument trays.

The invention discloses an ultra-high dose rate radiotherapy plan optimization system based on compensator modulation, and relates to the technical field of radiotherapy. A data acquisition module is used for acquiring medical image data of a patient and receiving a clinical target; the clinical target comprises a target region prescription dose, an organ-endangering limit and a minimum dose rate threshold value required for triggering and maintaining a FLASH effect; and the FLASH biological effect evaluation module is used for calculating FLASH biological effective dose distribution corresponding to the physical dose distribution through an embedded biological effect model based on the input physical dose distribution and dose rate distribution. According to the method, the physical dose is converted into the accurate FLASH biological effective dose through the improved linear quadratic model embedded with the FLASH correction factor, the target tumor killing effect is guaranteed, normal tissue protection is enhanced with the help of the tissue differentiation correction factor, the industrial pain point that the physical dose reaches the standard but the biological effect does not reach the expectation is effectively solved, and the application prospect is wide. And the treatment plan better meets the clinical curative effect and safety core requirements.

Carriers for embodying radioactive seeds, as well as a device for loading and customizing brachytherapy carriers based on the principles of optimizing a more precise and predictable dosimetry, and adaptable to the geometric challenges of a tumor bed in a real-time setting. The present disclosure relates to a specialized loading device designed to enable a medical team to create a radionuclide carrier for each patient and tumor reliably, reproducibly and efficiently.

The invention relates to DICOM image processing, in particular to a DICOM image preprocessing and quality control system based on Spark, and the system comprises a data collection module which collects a DICOM medical image from a data source, and automatically recognizes and extracts a key metadata field in the DICOM medical image; the index construction module is used for constructing a comprehensive and accurate index system according to key metadata fields of the DICOM medical images; the data standardization module is used for carrying out standardization processing on key metadata fields of the DICOM medical images, supporting version control and audit tracking on the key metadata fields and carrying out optimization processing on the DICOM medical images; the scoring module is used for carrying out objective quality evaluation on the DICOM medical image based on a multi-dimensional image quality evaluation model and calculating a corresponding comprehensive quality score; according to the invention, the defect that the DICOM medical images from different equipment manufacturers are difficult to efficiently preprocess can be overcome.

A method of priming an interventional device assembly includes providing the interventional device assembly, the interventional device assembly including a first interventional device and a second interventional device, the second interventional device being positioned within the first interventional device. The method further includes reciprocally moving at least one of the first interventional device and the second interventional device relative to the other of the first interventional device and the second interventional device while flushing a lumen between the first interventional device and the second interventional device with fluid to remove microbubbles from the lumen.

A system is disclosed including an ablation probe that includes an antenna, a display, and a controller in communication with the ablation probe and the display. The controller comprises a memory and is operable to receive first and second inputs indicative of an amount of time and a power level, respectively, to energize the ablation probe, retrieve, from the memory, a predicted ablation zone corresponding to the first and second inputs, display, on the display, an image representative of the ablation probe, and overlay, on the image, the predicted ablation zone, energize the ablation probe at the power level, and dynamically overlay, on the image, a progressive ablation zone based on the ablation probe being energized, wherein a size of the progressive ablation zone is retrieved from the memory based on the amount of time the ablation probe has been energized at the power level.

The invention relates to the technical field of oral health monitoring, and discloses a real-time oral health monitoring system based on an intelligent imaging technology. The system comprises an image capture module, a feature analysis module, a health parameter calculation module, an anomaly detection module and a feedback control module. The image capture module captures dynamic image data in the oral cavity in real time and transmits the data to the feature analysis module; the feature analysis module preprocesses the image data, identifies key oral cavity structural features and generates a structured feature data set; the health parameter calculation module quantifies related health parameters based on the data set and integrates the related health parameters into an oral health parameter set; the anomaly detection module identifies the oral cavity area with the parameter value deviating from the normal range and outputs an anomaly detection result set; and the feedback control module generates optimization suggestions according to the optimization suggestions and drives the user interface display module to output a visual report. According to the system, real-time monitoring, automatic analysis and timely feedback of oral health are realized, and the monitoring efficiency and accuracy are improved.

A system may detect a triggering condition by an imaging device. The system may capture, by the imaging device in response to the triggering condition, an image of a container. The system may perform, by a machine learning model, pixel quantification of the container. The system may determine, based on the pixel quantification, a status of the container.

The invention discloses a cross-modal gating fusion radiology report generation method combined with clinical semantic enhancement, and relates to the technical field of medical report generation. A semantic enhancement decoding unit is used for performing deep fusion on image sequence representation, historical text embedding and clinical semantic representation to obtain final enhancement decoding representation of multi-modal semantic enhancement; and performing report generation on the final enhanced decoding representation output by the semantic enhanced decoding unit to obtain a predicted radiology report. The predicted radiology report generated by the radiology report generation method is closer to a radiology report sample text in the aspects of sentence structure and coherence.