45 results about "Functional image" patented technology

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.

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.

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.

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.

The invention provides a radiotherapy plan generation method and device, equipment and a medium, and the method comprises the steps: determining a function change index of a target part of a target object based on a current function image of a current fraction and a historical function image of a historical fraction; under the condition that the function change index exceeds a preset index threshold value, determining current dose information and future dose information based on historical dose information, the current function image, the historical function image and the current function partition result; and based on the current dose information, generating a radiotherapy plan of the current fraction, and based on the future dose information, generating a radiotherapy plan of the future fraction. By applying the embodiment of the invention, the doses of different areas of the target part can be adjusted in time according to the already occurring functional state change or the impending functional state change of the target part in the multi-fraction radiotherapy process, and the radiotherapy plan is automatically adjusted, so that the risk of radioactive injury can be reduced, and the targeted protection of the target part is realized.

The application provides a liver tumor ablation robot system based on image and in-situ fluorescence fusion navigation. The system is applied to the field of medical robots and interventional treatment and comprises an image data analysis module, a tumor activity probability map is constructed and output based on patient functional image data; an intelligent ablation needle, in the ablation process, fluorescence signals of the tissue around the ablation focus are collected in-situ at the needle tip; a multi-degree-of-freedom collaborative mechanical arm, which is used for controlling the intelligent ablation needle to perform puncture and ablation operation; a fluorescence signal processing and real-time classification model, which is used for extracting fluorescence kinetic characteristics from the fluorescence signals and outputting tissue state classification results in real time; a navigation and control console, which is used for fusing the tumor activity probability map and the tissue state classification results to generate an augmented reality navigation interface and controlling the intelligent ablation needle to perform the time sequence of ablation and signal collection. Thus, the problems of difficult identification of active lesions, difficult dynamic tracking and lack of intraoperative feedback in a complex background are solved.

This invention belongs to the field of medical image processing technology, and more specifically relates to a multimodal image classification method, device, and computer-readable storage medium for auxiliary diagnosis of Parkinson's disease. The method includes acquiring an image; performing local normalization processing on the image to extract local normalization coefficients; fitting the local normalization coefficients to obtain shape parameters and variance; fitting the normalization coefficients, including shape parameters and variance, in each direction of the image using an asymmetric generalized Gaussian function to obtain index features in each direction; using a support vector machine as a regression model to obtain the image quality score; and comparing the image quality score with a set threshold. This invention solves the problem in the prior art that structural images have high resolution and can reflect structural morphological information, but weak metabolic and other functional information, while functional images have low resolution, can reflect functional metabolic information, but have difficulty reflecting structural information.

The application provides a kind of MCI diagnostic system based on multiscale hypergraph network, storage medium and electronic equipment, it is related to neural network technical field.In the present application, first, the fMRI signal of the patient to be diagnosed is preprocessed, and the BOLD time sequence of each ROI region on the functional image is obtained;Then calculate the phase synchronization relationship of ROI region in the spectral domain by the phase locking value technique;And use the graph attention mechanism to dynamically learn and identify the relative importance between different brain regions in the time domain;Then design a multiscale feature fusion mechanism to integrate the time domain and spectral dynamic connection features of fMRI signal, form a time-frequency fusion matrix, and establish a dynamic hypergraph model based on the matrix;Finally, a detection model for mild cognitive impairment is constructed using a hypergraph neural network, and the parameter optimization is carried out through a grid search strategy to improve the MCI diagnosis effect.

The application relates to the technical field of medical rehabilitation, in particular to a medical image feature extraction system for orthopedic postoperative rehabilitation tracking, which comprises the following units: a data acquisition and preprocessing unit, which is used for acquiring multi-modal medical image data and pre-processing the multi-modal medical image data; a static image processing unit, which is used for determining a bone healing quality index of a bone healing core area according to pre-processed static anatomical images; a dynamic image processing unit, which is used for determining a bone and soft tissue coordination index according to pre-processed dynamic functional images; a comprehensive pathology evaluation unit, which is used for determining a comprehensive pathology index according to the bone healing quality index and the coordination index; and a classification unit, which is used for determining a postoperative rehabilitation state classification according to the comprehensive pathology index. The application realizes the objectification of the evaluation process and the precision of the classification result by converting multi-modal image features into quantitative rehabilitation state classification results.

The application discloses a kind of dual-energy imaging method and system based on sparse acquisition optimization, belong to X ray imaging technical field.The method includes: the complete projection data of non-sparse in low-energy or high-energy mode is collected as the first circle data, and the sparse angle projection data in high-energy or low-energy mode is collected as the second circle data;Using projection domain base material decomposition algorithm, the base substance projection decomposition result under sparse angle is obtained;The base substance decomposition result under sparse angle is interpolated and completed, the error between the calculated value and the true value of low-energy projection data under non-sparse acquisition is optimized by grid search, to obtain the corrected non-sparse angle base substance decomposition result;The required functional image is output.The application introduces corresponding algorithm process while realizing sparse acquisition, reduces the error in angle completion process, while guaranteeing the advantage of sparse acquisition, realizes the improvement of material decomposition precision.

The present invention discloses a device for acquiring a functional image of tissue and a method for acquiring a functional image by using same, the device comprising: a light source for irradiating a tissue to be imaged with coherent light; an image acquisition unit for acquiring an image of a speckle pattern which is formed by scattering the light emitted from the light source over the tissue, and acquiring multiple images having different exposure times; an image processing unit for generating a functional image of the tissue on the basis of the multiple images acquired by the image acquisition unit; and a control unit for adjusting the light quantity of the light emitted to the tissue such that the multiple images having different exposure times have brightness values in a common range, and controlling the operation of the image acquisition unit.

The invention discloses a functional image generation method based on a single-energy CT image and related equipment, and relates to the field of medical image processing. The method comprises the following steps: acquiring a to-be-processed single-energy CT image, and a previous frame of CT image and a next frame of CT image which are adjacent to the single-energy CT image in an original CT data set along a layer scanning sequence; combining the single-energy CT image, the previous frame of CT image and the next frame of CT image into first multi-channel input data according to a preset channel arrangement rule, and inputting the first multi-channel input data into a first-stage network to obtain an electron density map, an effective atomic number map and an iodine concentration map corresponding to the single-energy CT image; and the single-energy CT image, the electron density map and the effective atomic number map form second multi-channel input data according to a preset channel construction mode, the second multi-channel input data is input to a second-stage network to obtain a blocking capability map corresponding to the single-energy CT image, and the second-stage network and the first-stage network adopt the same network architecture. The functional image is generated through the single-energy CT equipment.