69 results about "Functional image" patented technology

The invention provides a digital information processing method for a hospital radiology department, which comprises the following steps: S1, multi-modal image collaborative acquisition and standardization: synchronously acquiring anatomical structure images, functional images and metabolic parameter data of a patient through radiology department imaging equipment, and converting the anatomical structure images, the functional images and the metabolic parameter data into space-time aligned three-dimensional digital matrixes; s2, image quality optimization processing: performing nonlinear contrast enhancement and noise suppression on the original image to improve the signal-to-noise ratio of a target area; s3, dynamic self-adaptive registration: according to the biomechanical characteristics of the organ, fusing the rigid transformation model and the elastic deformation model, and according to the digital information processing method for the hospital radiology department, based on the dynamic registration matrix of the biomechanical model, improving the multi-modal image fusion precision; a deep learning segmentation algorithm fused with morphological constraints improves the focus boundary recognition accuracy; a texture mapping three-dimensional reconstruction technology is mixed, and an anatomical structure and metabolism information are presented at the same time; the invention discloses a structured report automatic generation system based on an attention mechanism.

Presented herein are systems and methods that provide for automated analysis of medical images to determine a predicted disease status (e.g., prostate cancer status) and / or a value corresponding to predicted risk of the disease status for a subject. The approaches described herein leverage artificial intelligence (AI) to analyze intensities of voxels in a functional image, such as a PET image, and determine a risk and / or likelihood that a subject's disease, e.g., cancer, is aggressive. The approaches described herein can provide predictions of whether a subject that presents a localized disease has and / or will develop aggressive disease, such as metastatic cancer. These predictions are generated in a fully automated fashion and can be used alone, or in combination with other cancer diagnostic metrics (e.g., to corroborate predictions and assessments or highlight potential errors). As such, they represent a valuable tool in support of improved cancer diagnosis and treatment.

The invention discloses a transcranial magnetic stimulation positioning system based on a deep effect brain region, and the system comprises the steps: obtaining the data of a tested magnetic resonance image, which comprises a resting state functional image and a high-resolution T1 structure image; performing data preprocessing on the function image and the structure image, and establishing an individual space; the deep effect brain region template is converted to an individual space through nonlinear registration, and a target region of interest is defined; calculating functional connections between voxels of the deep effect brain region and the cortical region by adopting a Granger causality analysis method based on wavelet transformation; and screening Top block masses according to the functional connection strength, calculating the gravity centers of the Top block masses, and determining individualized stimulation targets in combination with the skull surface distance. According to the method, spontaneous brain activity function variation of the brain of an individual and the brain signal propagation direction are fully considered, accurate positioning of different individual levels is achieved, relatively stable cortex stimulation targets are obtained, and therefore the clinical curative effect of TMS is optimized.

The invention relates to the technical field of stereotactic surgery, and discloses a neurosurgery stereotactic surgery positioning system based on multi-modal image fusion, which comprises a multi-modal image acquisition module, an intelligent registration fusion module, a three-dimensional modeling module, a surgery navigation engine, an augmented reality interface and a dynamic calibration module, a cross-modal elastic registration module is arranged, when multi-modal image fusion is carried out, the spatial matching degree of a functional image and a structural image is detected in real time through a nonlinear deformation compensation algorithm, and when registration deviation exists between white matter fiber bundles and tumor boundaries, an elastic deformation compensation field is dynamically generated by a system, so that the positioning accuracy of a neural functional area is improved; and by arranging the dynamic drift correction module, the brain tissue displacement change is perceived in real time based on laser surface scanning during deep target navigation, precise correction of the pose of the surgical instrument is realized, and the positioning reliability of the deep target is ensured.

The invention belongs to the technical field of optical imaging, and discloses a multifunctional image edge enhancement device based on spiral phase contrast imaging, which comprises a light source system, an optical imaging system and an edge enhancement detection system which are arranged in sequence, the light source system is used for generating collimated linear polarization laser; the optical imaging system comprises a first 4-f system and a round hole diaphragm which are sequentially arranged on a light path; a sample to be tested is arranged between the light source system and the first 4-f system; the edge enhancement detection system comprises a first lens, a vortex wave plate, a second lens and an imaging unit which are sequentially arranged on a light path; the first lens and the second lens form a second 4-f system; linearly polarized laser output by the light source system is transmitted by a to-be-detected sample, enters the first lens after passing through the first 4-f system and the round hole diaphragm, and then is imaged on the imaging unit after passing through the vortex wave plate and the second lens in sequence. According to the invention, edge enhancement can be realized, and the contrast and resolution of the image are improved.

The invention discloses a method for predicting the curative effect of brain stimulation on MCI based on a multi-modal image, and belongs to the technical field of medical data process.The method comprises the steps that through a multi-modal MRI feature fusion model, structure and functional MRI indexes are synchronously integrated, feature selection and dimension reduction are conducted through comparison between independent sample t test groups and LASSO regression, and the curative effect of brain stimulation on MCI is predicted; compared with the existing method, the method has the advantages that the obvious contribution of the change of the collaborative structure image index and the functional image index to the predicted curative effect is verified through the structure-function coupling analysis, and the prediction model is constructed, so that the prediction efficiency is improved. The contribution direction and strength of each image feature to curative effect prediction are analyzed and quantified in combination with SHAP values, feature weights are automatically optimized according to SHAP value distribution, and model high-contribution feature brain regions are revealed through SHAP so as to clarify curative effect biomarkers.

Computer implemented methods and systems for functional image compression disclosed herein are techniques to overcome computational limitations for the storage and analysis of large amounts of image data. The disclosed techniques provide compressed versions of image data that are amenable to image reconstruction and directly applicable to data analysis algorithms.

The invention provides a radiotherapy plan generation method and device, equipment and a medium, and the method comprises the steps: obtaining a target function image of a target object; the target function image comprises a target region, an organ at risk and a target part; determining target dose information of the target part based on the target function image, the target function partitioning result, the target region segmentation result and the endangered organ segmentation result; the target function partitioning result is used for indicating spatial distribution of a plurality of functional regions of the target part divided according to the functional state, and the target dose information comprises doses of different regions of the target part; and generating a radiotherapy plan based on the target dose information. By applying the embodiment of the invention, the set dose information of the target part is more reasonable, so that the radiotherapy plan generated based on the target dose information can ensure the accuracy of tumor control, reduce the risk of radioactive injury and realize targeted protection of the target part.

The invention discloses an interactive lattice radiotherapy planning method and system based on a functional image, and relates to the technical field of radiotherapy, and the method comprises the steps: obtaining a radiotherapy positioning CT image of a patient and a functional metabolism image after the space registration with the radiotherapy positioning CT image; based on the radiotherapy positioning CT image and a preset safety boundary parameter, determining a candidate area of lattice layout in the tumor target area; for each candidate position in the candidate region, adaptively calculating lattice parameters for the position based on the corresponding SUV value of the position in the functional metabolism image; determining a final lattice center set from the candidate positions through an iterative screening algorithm on the basis of the calculated lattice parameters of the candidate positions and preset geometric constraints and biological constraints, and generating a lattice target region set on the basis of the final lattice centers and the lattice diameters corresponding to the final lattice centers; and outputting the lattice target region set for dose calculation of a radiotherapy planning system. Individualized dosage improvement really based on tumor internal heterogeneity is achieved.

The invention provides a dose optimization method and device, equipment and a medium, and the method comprises the steps: obtaining a functional image of a target object and the initial dose information of a target part; the functional image comprises a target part, and the initial dose information comprises initial doses of different areas in the target part; determining a damage prediction result of the target part through a pre-trained damage prediction model based on the functional image and the initial dose information; the damage prediction result is used for indicating the probability of radioactive damage at each position in the target part; based on the damage prediction result, optimizing the initial dose information to obtain target dose information of the target part; the target dose information comprises target doses of different areas in the target part. By applying the embodiment of the invention, the dose optimization effect can be ensured, the risk of radioactive injury of the target part is reduced, and the protection effect on the target part is improved.

The invention belongs to the technical field of image processing, and discloses a hepatobiliary calculus surgery image navigation and positioning system, which is configured to realize non-rigid registration of adaptive multi-stage fusion, dynamically adjust registration weights of surface and deep features according to environmental changes in surgery, and realize image navigation and positioning of the hepatobiliary calculus surgery. It is ensured that a continuous high-precision dynamic three-dimensional model is provided in the whole process; predictive virtual tactile feedback based on biomechanical simulation is realized, and tissue tension perception and damage early warning beyond real tactile sense are provided for doctors by calculating stress and strain of a tissue model in real time; the intelligent quantification of the stone residual risk based on multi-source information fusion is realized, and the stone residual risk is quantified and visualized with high confidence by fusing the surgical operation history and the intraoperative fluorescence function image. According to the invention, a closed-loop navigation platform integrating high-precision environment perception, predictive process control and intelligent result quality control is constructed, and the precision and safety of auxiliary tools for minimally invasive surgery of hepatic duct calculi are improved.

The invention relates to a Parkinson's disease motion symptom auxiliary diagnosis system based on multi-modal artificial intelligence, and belongs to the field of medical AI auxiliary diagnosis. The system integrates multi-modal image data, and realizes common symptom classification and severity degree scoring of four motion symptoms of Parkinson's disease through preprocessing, multi-modal feature extraction combined with a 3D CNN branch and a Vision Transform branch, causal feature screening based on an IAMB algorithm, and a multi-modal fusion and multi-task learning module. The system can effectively fuse structure and functional image information, improves diagnosis accuracy and interpretability, is especially suitable for early symptom identification and quantitative evaluation, and has high clinical practical value.

The invention relates to a cerebral cortex metabolism visualization method and system. The method comprises the steps of obtaining a first functional image and a structure image of the brain of a target patient; based on the target neural network model, performing denoising processing on the first functional image to obtain a second functional image; wherein the target neural network model is obtained by training an initial neural network model based on a sample set, the sample set comprises multiple groups of samples, and each group of samples comprises a first functional image sample and a structure image sample of the brain of a sample patient; generating a three-dimensional grid model of the cerebral cortex according to the structure image; and mapping the metabolic information in the second functional image into the three-dimensional grid model, and visualizing the metabolic information in the three-dimensional grid model. By adopting the method, accurate correspondence and visual fusion expression of the brain anatomical structure information and metabolism information of the target patient can be realized, and the observation efficiency of a doctor is improved.

A method for determining a convolution kernel for an iterative statistical algorithm based on a continuous-to-continuous data model. The method is used for image reconstruction from radiation measurements obtained in emission tomography, specifically in a Time-of-Flight Positron Emission Tomography (TOF PET) scanner. The presented method is a non-list-mode solution that reduces the computational complexity of the reconstruction problem, improves the resolution of reconstructed images, reduces the radiation dose absorbed by patients during TOF PET examinations, and / or shortens the measurement acquisition time without significantly compromising the quality of the diagnostic images. Notably, the quality of the functional images remains at the same level. These improvements are achieved by designing the convolution kernel to account for the statistical properties of the measurement signals registered during the TOF PET scanner's acquisition process.

The invention belongs to the field of biomedical engineering, and discloses a function positioning system for connection of a medial thalamic pillow and an emotional cortex, which comprises the following steps of: performing near-infrared nerve stimulation on the medial thalamic pillow, and collecting an MRI (Magnetic Resonance Imaging) structure image and an MRI function image during stimulation; according to the MRI structure image, projecting a buckling back, a brain island, an amygdaloid nucleus and a subregion thereof, and a brain region adjacent to the buckling back, and respectively segmenting the buckling back, the brain island and the amygdaloid nucleus; different body emotion expression function partitions are positioned at the buckle back; positioning the internal sensory function subareas according to the subareas of the brain island; according to different subregions of the amygdala kernel, positioning the emotion function regions of the amygdala kernel; according to the MRI functional image, the activated voxel is evaluated, and according to the positions of the activated voxel in different emotional loop brain areas, the function positioning of the connection of the inner thalamic pillow and the emotional cortex is realized. According to the system, the specific topological connectivity of the inner thalamic pillow and the brain emotional cortex is realized.

This invention relates to the field of medical image processing, specifically to a multimodal medical image fusion system and method, comprising a data preprocessing module, a domain manifold embedding module, a hierarchical adaptive domain alignment network module, a multimodal feature fusion module, and a diagnostic decision module. The system establishes a topological correspondence between EBUS ultrasound, OCT tomography, and DWI functional images through a multidimensional domain manifold embedding structure; employs a hierarchical adaptive domain alignment network to achieve multi-scale feature extraction and precise alignment; designs a topology-preserving multimodal feature fusion mechanism to ensure the complete preservation of key diagnostic information from each modality during the fusion process; and utilizes a dual-path cross-validation decision strategy to improve the stability and reliability of diagnosis. The system inputs the domain-aligned multimodal features into a Transformer network and generates nodule detection and benign / malignant classification results through dual-threshold judgment, achieving accurate and non-invasive diagnosis of small lesions such as pulmonary nodules and early gastrointestinal lesions.

The application provides a voxel-level radionuclide dose estimation method based on radionuclide imaging and a computer device. The method comprises the following steps: acquiring X-ray structural images and gamma-ray functional images at a single time point or multiple time points; segmenting a region of interest to obtain multiple sub-regions of interest; performing regional partial volume correction on the multiple sub-regions of interest of the gamma-ray functional images to obtain corrected gamma-ray functional images; performing registration on the corrected gamma-ray functional images; performing activity-dose rate conversion on the registration results to obtain a dose rate, and performing voxel-level curve fitting and integration on the dose rate to obtain an absorbed dose distribution result, and determining the absorbed dose of each sub-region of interest based on the absorbed dose result. The application can reduce the influence of the partial volume effect on the resolution of radionuclide imaging, improve the accuracy of radionuclide image registration, and further improve the accuracy of radionuclide absorbed dose estimation.

The invention discloses a radiotherapy plan evaluation information processing method and system based on a biological effect dose and a functional image. The method comprises the following steps: acquiring a CT image of a patient, structural contour information of a tumor or a normal tissue region of interest in the CT image, a radiotherapy physical dose distribution matrix and radiotherapy plan prescription information; querying to obtain physical doses corresponding to all pixel points in the region of interest of the tumor or the normal tissue in the CT image, and calculating biological effect doses of all the pixel points; acquiring a functional image reflecting biological characteristics of tumors or normal tissues of the patient; calculating weighted function distribution information of each pixel point in a tumor or normal tissue region of interest in the CT image; and calculating a biological effect dose-function histogram of the region of interest to be evaluated for evaluating the radiotherapy plan. According to the method, the biological effect dose and functional heterogeneity of the region of interest to be evaluated are reflected, and individualization and accuracy of radiotherapy plan evaluation can be improved.

1. Name of the product in this design: Near-infrared brain functional imaging device probe adapter. 2. Purpose of this design: This design is used in a near-infrared brain function imaging device, in conjunction with a near-infrared probe, to fix the near-infrared probe onto the head cap of the near-infrared brain function imaging device. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the key design points: Design 1 3D view. 5. Design 1 is designated as the basic design.

The application relates to the field of stereotactic surgery technology, and discloses a neurosurgical stereotactic surgery positioning system based on multi-modal image fusion, which comprises a multi-modal image acquisition module, an intelligent registration and fusion module, a three-dimensional modeling module, a surgery navigation engine, an augmented reality interface and a dynamic calibration module; through the setting of the cross-modal elastic registration module, when the multi-modal image fusion is carried out, the spatial matching degree of functional images and structural images is detected in real time through a nonlinear deformation compensation algorithm; when there is a registration deviation between the white matter fiber bundle and the tumor boundary, the system dynamically generates an elastic deformation compensation field, the positioning accuracy of the functional area is improved, and the risk of functional area cutting is reduced; through the setting of the dynamic drift correction module, when deep target point navigation is carried out, the brain tissue displacement change is sensed in real time based on laser surface scanning, the accurate correction of the position and posture of a surgical instrument is realized, and the reliability of deep target point positioning is ensured.

This invention discloses a multimodal medical image fusion method based on a global optimization model, comprising: acquiring registered image pairs: anatomical medical images as grayscale images and functional images as three-channel color images; inputting the extracted illumination component of the functional image and the single-channel grayscale image into the image module of global optimization decomposition respectively to obtain their corresponding base layer and detail layer; fusing the obtained base layer and detail layer respectively; linearly adding the obtained fused base layer and fused detail layer to obtain the fused illumination component; and merging the new illumination component with the color component of the input functional image to obtain the final fused image. This invention effectively solves the uncertainty of parameter selection in medical image fusion algorithms and directly obtains the ideal fused image through an optimization function method.

Systems and methods are provided that include acquiring, at a plurality of different times, an induced voltage within a plurality of coils arranged about the subject's head and positioned within a variable magnetic field. The method also includes acquiring electroencephalogram (EEG) data from a plurality of EEG sensors, wherein each EEG sensor is paired with a respective one of the plurality of coils. The method also includes determining, for each of the plurality of times, a position of each coil in the plurality of coils positioned in the variable magnetic field utilizing the induced voltage at the particular time and using the position of each coil in the plurality of coils to correlate the EEG data with at least one of an anatomical image or a functional image of the head of the subject.

A medical image processing apparatus includes processing circuitry. The processing circuitry obtains a morphological image and a functional image including at least a predetermined anatomical structure of a test subject; obtains reference morphological data and reference functional data corresponding to the morphological image and the functional image, respectively; individually segments the morphological image and the reference morphological data according to a function of interest appearing on the functional image; segments the functional image with reference to the segmental morphological images, and segments the reference functional data with reference to the segmental reference morphological data; performs a first registration process for aligning the segmental morphological images and the segmental reference morphological data with each other; and performs a second registration process for aligning the segmental functional images and the segmental reference functional data with each other according to a result of the first registration process.

A system (102) includes a spatial mismatch correction module (168) configured to receive functional transmission data, anatomical image data, and functional image data that is reconstructed based on the functional transmission data and attenuated based on the anatomical image data. The system also includes a dataset provider (502) configured to provide the first dataset and the second dataset that are spatially mismatched. The system also includes a voxel-of-interest identifier (512) configured to identify voxels or regions of reconstruction inconsistency due to a spatial mismatch between a real attenuation value and an attenuation value derived from the anatomical image data based on a relationship between the first data set and the second data set. The system also includes an image data generator (614) configured to deform the functional image data based on the identified voxels or regions and generate corrected functional image data independent of the functional-anatomical correlation while maintaining image quality of the functional image data.

To provide a display control device for a vehicle capable of changing a state of an operation function of an own vehicle by an intuitive operation to a display area.SOLUTION: The vehicular display control device 10 includes the display controller 52 that displays the own vehicle image simulating the own vehicle and the function image indicating the operating function of the own vehicle in the display area provided around the driver's seat of the own vehicle, and moves the display of the function image according to the operation on the function image, and the function controller 54 that controls the state of the operating function corresponding to the operated function image based on the positional relationship between the own vehicle image and the function image.SELECTED DRAWING: Figure 2

The invention discloses a multi-mode image detection device. The multi-mode image detection device comprises a rack; the PET detection module, the CT detection module and the ion treatment module are arranged on the rack, and at least one part of the PET detection module, at least one part of the CT detection module and at least one part of the ion treatment module are located in the same detection ring during detection. According to the application, the requirement of a patient for transferring and positioning among different devices can be eliminated, system errors caused by transferring and positioning can be eradicated, synchronization or near synchronization of treatment and functional image acquisition can be realized, real-time biological feedback information can be obtained, the overall treatment time can be greatly shortened, and the turnover efficiency of a treatment room and the medical experience of the patient can be improved.

The application discloses a kind of based on computer vision OpenCV extraction building contour and planar functional feature method, including original image is preprocessed and edge detection, obtain initial edge image, carry out binary and contour search, multiple candidate contours are geometrically approximated and screening processing, according to screening result determine the final building outer contour;Input functional image containing building internal functional partition, and carry out color space conversion and threshold segmentation, binary mask is morphologically processed and contour search, determine the contour of each functional area, according to preset rule, functional area is labeled;The extracted functional area is clustered and analyzed, and the analysis result containing functional contour, area statistics and appearance probability is output.The application can shorten the time of single building contour extraction and single household planar function analysis from day level, hour level to second level to minute level, improve the efficiency of building design, effectively overcome the defects of low efficiency and long cycle of manual operation.

The invention provides a voxel-level nuclide dose estimation method based on nuclide imaging and computer equipment. Comprising the following steps: acquiring an X-ray structure image and a gamma-ray function image at a single time point or a plurality of time points; segmenting the region of interest to obtain a plurality of sub-regions of interest, and performing region-level partial volume correction on the plurality of sub-regions of interest of the gamma-ray functional image to obtain a corrected gamma-ray functional image; carrying out registration on the corrected gamma ray function image; and performing activity-dose rate conversion on the registration result to obtain a dose rate, performing voxel-level curve fitting and integration on the dose rate to obtain an absorbed dose distribution result, and determining the absorbed dose of each sub-region of interest based on the absorbed dose result. According to the method and the device, the influence of partial volume effect on nuclide imaging resolution can be reduced, so that the nuclide image registration precision is improved, and the radionuclide absorbed dose estimation precision is improved.

A method for determining a convolution kernel for an iterative statistical algorithm based on a continuous-to-continuous data model for image reconstruction from radiation measurements obtained in emission tomography, specifically in a Positron Emission Tomography (PET) scanner. The method improves the resolution of reconstructed images, reduces the radiation dose absorbed by patients during PET examinations, and / or shortens the measurement acquisition time without significant loss in the quality of the diagnostic images obtained. Specifically, the quality of the functional images remains at the same level. These improvements are achieved through the design of the convolution kernel, which takes into account the statistical properties of the measurement signals registered during the acquisition process in the PET scanner.