136 results about "Functional imaging" patented technology

Presented herein are systems and methods for the automated determination of a prostate cancer staging score (e.g., a PRIMARY score) for a subject. In certain embodiments, the systems and methods employ a machine learning model (e.g., one or more convolutional neural networks, CNNs) to analyze three-dimensional (3D) images obtained via both a functional imaging modality and an anatomical imaging modality. In addition to identifying regions of PSMA binding agent uptake (hotspots), the techniques described herein are able to accurately and automatically associate specific prostate zones to each hotspot and use this information in the determination of the staging score.

A user workload state processing method and apparatus based on multimodal data, and a device. The method comprises: acquiring state information of a first user; determining workload information of the first user on the basis of the acquired state information, wherein the state information comprises at least two of the following information: physiological information, eye movement information, electroencephalogram information, brain function imaging information, motion capture information, spatiotemporal acquisition information, behavior acquisition information, and facial expression and state information; and feeding back the workload information to a first management account, and formulating a training scheme matched with the workload information. According to the embodiments of the present application, workload of users can be identified on the basis of multimodal data of users.

A system for automated programming of stimulation devices uses machine learning with multimodal medical imaging data to determine optimal patient-specific parameters. The system stores voxel-level intensity and functional imaging data from patients who previously underwent stimulation therapy. Similarity metrics calculated directly between the raw imaging data are used to cluster patients into phenotypic groups. Known therapeutic outcomes for each patient are linked to the associated stimulation parameters. For a new patient, biomarkers are extracted from their medical imaging data and used to identify phenotypically similar groups. The stimulation parameters with beneficial outcomes in those groups are analyzed to determine target recommended settings or discard suboptimal settings for the new patient. This data-driven approach leverages machine learning on multimodal medical imaging to automate patient-specific programming of stimulation therapy devices for optimal therapeutic benefit without requiring spatial normalization or atlas registration.

The invention relates to a functional imaging noise reduction and registration method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring an original video sequence, and preprocessing the original video sequence; extracting a set number of continuous video frames from the preprocessed video sequence, inputting the continuous video frames into a Vi deoSD network, and carrying out network training by taking an intermediate frame after outputting noise reduction and registering with front and rear frames as a training target to obtain a trained noise reduction registration network; and extracting a set number of continuous video frames from the video sequence to be processed, replacing an intermediate frame in the continuous video frames with a set template frame, inputting the intermediate frame into the trained noise reduction registration network, and outputting the intermediate frame which is subjected to noise reduction and registration with the fixed frame through the noise reduction registration network. According to the method, denoising and registration are used as two correlated tasks for training at the same time, so that the denoising and motion calibration effects can be improved, and meanwhile, the data processing efficiency is improved.

The invention relates to the technical field of health risk assessment, in particular to a neurosurgery risk prediction method and system based on big data analysis, and the method comprises the steps: obtaining the neural signal intensity of a brain region in preoperative functional image data of a patient, analyzing the balance degree of neural signal transmission, and analyzing the balance of oxygen metabolism distribution according to the nerve conduction rate. And preoperative nerve state information is formed. According to the method, by accurately extracting the preoperative neural activity signals and analyzing the signal transmission delay, the fluctuation amplitude and the oxygen metabolism balance, the accuracy of individual neural function state evaluation is improved. In the postoperative recovery stage, the abnormal region is dynamically recognized in combination with the neural signal change trend, and the metabolism matching capacity is evaluated, so that the recovery mode is more refined. Neural network connection adjustment capability analysis enhances signal transmission stability evaluation, and abnormal region identification accuracy is improved by combining time deviation and oxygen metabolism recovery consistency.

The invention relates to the technical field of medical image processing, and discloses a brain network image analysis method, system and device for a glaucoma patient and a medium, and the method comprises the steps: carrying out the brain region scanning of the glaucoma patient, and obtaining a high-resolution structure image, a resting state function image and a diffusion tensor image; pre-processing the resting state function image and the diffusion tensor image, and respectively registering the resting state function image and the diffusion tensor image with the high-resolution structure image to obtain a registered resting state function image and a registered diffusion tensor image; performing brain region division on a glaucoma patient, wherein each region is used as a node; on the basis of registration resting state functional imaging, Pearson's correlation coefficients between the nodes are calculated to construct a whole-brain functional network; on the basis of registration diffusion tensor imaging, the number of fiber bundle connections between nodes is calculated to construct a whole-brain structure network; and carrying out coupling analysis on the whole brain function network and the whole brain structure network to obtain an F-S coupling coefficient. The method is helpful for deeply researching the influence of glaucoma on the brain network.

The invention discloses a focused ultrasound transcranial nerve regulation and control platform and method based on photoacoustic imaging. The system comprises a synchronous pulse generator, a pulse ultrasound transmitting system, a photoacoustic signal collecting system and a fixing device. According to the method, the limitation of other imaging monitoring modes is overcome, monitoring is carried out by utilizing the characteristics of non-invasiveness, high resolution and high contrast of photoacoustic imaging, the TUS progress can be monitored for providing real-time dynamic imaging, and functional information can be provided; photoacoustic imaging is applied to focused ultrasound transcranial nerve regulation for the first time. And meanwhile, by utilizing high sound resolution and high optical contrast of photoacoustic imaging, the strongest photoacoustic signal can be provided in a near-infrared region for hemoglobin of a seat endogenous contrast agent, so that the PAT becomes an ideal imaging tool for detecting cerebral hemodynamics. In addition, key pathophysiological parameters are evaluated through functional imaging provided by the PAT, and the method can be used for evaluating brain changes in the low-intensity focused ultrasound stimulation process.

Disclosed herein are systems and methods for adapting and / or updating radiotherapy treatment plans based on biological and / or physiological data and / or anatomical data extracted or calculated from imaging data acquired in real-time (e.g., during a treatment session). Functional imaging data acquired at the time of radiation treatment is used to modify a treatment plan and / or dose delivery instructions to provide a prescribed dose distribution to patient target regions. Also disclosed herein are methods for evaluating treatment plans based on imaging data acquired in real-time.

The invention relates to a gradient-based tactile topology mapping model construction method. The method comprises the steps of obtaining functional imaging data and structural imaging data of magnetic resonance scanning of a testee; constructing a voxel-level functional connection matrix based on a voxel space in the functional imaging data; constructing a vertex-level structure connection matrix based on a cortex space in the structure imaging data; based on a gradient dimension reduction analysis processing method, matrix similarity calculation and dimension reduction analysis are carried out on the function connection matrix and the structure connection matrix, and a plurality of gradient components and variance interpretation quantities are obtained; and on the basis of the variance interpretation quantity, determining a functional main gradient and a second structural gradient, and constructing a tactile topology mapping model in combination with a tactile topology distribution rule. According to the method, the problem that the current tactile perception topological mapping is not accurate is solved, and more accurate mapping of tactile perception and brain activation is realized.

The invention provides a pathological target positioning method and system based on time domain interference stimulation. The method comprises the steps that electroencephalogram data, functional image data and structural image data of a patient are acquired; generating a spatial distribution diagram according to the electroencephalogram data and the structure image data; performing registration processing on the spatial distribution diagram and the functional image data to obtain the spatial distribution diagram and the functional image data after registration processing; the spatial distribution map after registration processing is matched with the spatial position of the functional image data; performing data fusion on the spatial distribution map and the functional image data after registration processing to generate a comprehensive brain function map; phase synchronism analysis is carried out on the comprehensive brain function map, the phase synchronism of different brain regions is evaluated, and the brain region with the phase synchronism larger than a preset threshold value and active in the cognitive task is determined as the pathological target region. According to the embodiment of the invention, the method can achieve the precise recognition and positioning of the AD core pathological target region, and facilitates the precise intervention of the AD core pathological target region.

The invention discloses a system for evaluating the cognitive function of a subject based on fNIRS and an interaction method. The head cap and the near-infrared light emitting / receiving probe in the system enable the imaging range to cover the frontal lobe, the temporal lobe and the occipital lobe; the cognitive assessment normal form interaction device sequentially executes a suppression control assessment normal form, an alert attention assessment normal form, a selection attention assessment normal form, a core attention network assessment normal form, a work memory assessment normal form and a cognitive control assessment normal form in a single block mode according to an execution sequence from simple to difficult; the signal acquisition device cooperatively acquires near-infrared brain function imaging time sequence data in the sequential execution process of each evaluation normal form; the processing device evaluates the cognitive function of the subject on the basis of the near-infrared brain function imaging time series data and behavioral data generated on the basis of the evaluation normal form. According to the method, the brain function data of more dimensions associated with the cognitive function can be acquired in a short time, and multi-angle evaluation and analysis on the cognitive function of the subject can be conveniently and clinically performed based on the fNIRS.

A sensory mapping method for a human brain is disclosed. The method includes the steps of flattening the cortical surface of the human brain, projecting functional imaging data onto the flattened surface, smoothing the functional imaging data, generating a sensory map, registering sensory maps across individuals and analyzing the maps in the common space. The flattening utilizes a conformal parametrization method. The smoothing utilizes a topological smoothing method that utilizes a diffeomorphic smoother. The registering is diffeomorphic. The sensory mapping method may further include a step of processing the functional imaging data to produce topological results.

The present invention belongs to the technical field of image processing, and specifically relates to a dual-channel joint reconstruction method based on a structured illumination microscope, including: obtaining dual-channel fluorescence images of organelles according to the structured illumination microscope; constructing a structure-function synchronous imaging model based on the dual-channel fluorescence images, where is the organelle structure information and is the organelle function information; adding a regularization term constraint of the organelle function information to the structure-function synchronous imaging model to obtain an objective function; iteratively optimizing the objective function to obtain the organelle structure information and function information; the present invention combines structure imaging and function imaging into the same objective function for modeling, realizes the synchronous reconstruction of structure information and function information, can better suppress reconstruction artifacts, and improve the fidelity; the present invention introduces continuous prior information into the reconstruction process, can better suppress the artifacts in the reconstructed super-resolution function information, and solve the reconstruction problem of low signal-to-noise ratio images.

This invention provides a transmembrane assessment system and method for three-dimensional bladder morphology, applied in the field of data processing technology. This application preprocesses bladder ultrasound image information of a target patient to generate target ultrasound image sequence information; processes the target ultrasound image sequence information to generate target enhanced ultrasound images; processes the patient's urinary system physiological parameters based on a target bladder morphology assessment model to generate target physiological state characteristics; processes the target physiological state characteristics, target enhanced ultrasound images, and functional imaging data based on the target bladder morphology assessment model to generate a predicted CT image of the target patient; and processes the predicted CT image and simulated localization CT image information of the target patient based on the target bladder morphology assessment model combined with bladder dynamic image information to generate a three-dimensional bladder morphology assessment result.

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 embodiment of the utility model provides an optical fiber cable and a near-infrared brain function imaging system with the same, the optical fiber cable comprises an optical fiber, a fabric layer and an outer sleeve layer, the fabric layer sleeves the optical fiber, and on at least a middle section of the optical fiber cable, the fabric layer can slide relative to the optical fiber at least along the longitudinal direction of the optical fiber; the extension degree of the fabric layer in the longitudinal direction is lower than a first threshold value; the fabric layer is sleeved with the outer sleeve layer, and the outer sleeve layer is light-proof and flexible. When the middle section of the optical fiber cable is subjected to sudden external force or is partially tightened, the fabric layer can firstly bear large external force, the optical fiber and the fabric layer slide relatively, and breakage or damage of the optical fiber caused by the fact that most force suddenly acts on the optical fiber can be prevented. Usually, relative sliding between the optical fiber and the fabric layer caused by holding the optical fiber cable by a user is avoided. Even if the optical fiber and the fabric layer cannot slide relatively, when the fabric layer is tightened, the optical fiber cannot be snapped due to the small extensibility of the fabric layer.

The present application discloses a system and interactive method for evaluating the cognitive function of a subject based on fNIRS. The head cap and near-infrared light emitting / receiving probe in the system enable the imaging range to cover the frontal lobe, temporal lobe, and occipital lobe; the cognitive assessment paradigm interactive device sequentially executes the inhibitory control assessment paradigm, the alert attention assessment paradigm, the selective attention assessment paradigm, the core attention network assessment paradigm, the working memory assessment paradigm, and the cognitive control assessment paradigm in a single-block mode in an order of execution from simple to difficult; the signal acquisition device collaboratively collects near-infrared brain function imaging time series data during the sequential execution of each assessment paradigm; the processing device evaluates the cognitive function of the subject based on the near-infrared brain function imaging time series data and the behavioral data generated based on the assessment paradigm. The present application can obtain brain function data of more dimensions associated with cognitive function in a relatively short period of time, which is convenient for clinical evaluation and analysis of the cognitive function of the subject from multiple angles based on fNIRS.

The application belongs to the technical field of material preparation, and relates to a bimodal functional imaging nanomaterial and a preparation method and application thereof. 1‑x Fe x Se2, wherein 0 < x < 1. The preparation method of the bimodal functional imaging nanomaterial comprises the following steps: stirring ferrous sulfate and cysteine in a solvent until uniform, then fully stirring bismuth salt, then adding sodium selenite to perform a heating reaction to obtain a bismuth iron selenium nanocomposite. The bismuth iron selenium nanocomposite provided by the application is uniform in size, regular in morphology, has good water phase dispersibility, and has the performance of simultaneously enhancing MRI imaging and CT imaging.

The utility model relates to an optical fiber probe for near-infrared brain function imaging detection. The optical fiber probe comprises a mounting base, a probe cap, a probe main body and a probe shaft cover, the mounting base is arranged on the detection helmet, and a mounting groove is formed in the mounting base. One end of the probe cap is connected with the fiber. The probe main body is arranged at the other end of the probe cap and penetrates through the mounting groove to be in contact with the head of a tester, and a limiting boss is fixedly sleeved on the probe main body. The probe shaft cover is movably sleeved between the limiting boss and the probe cap and is in threaded connection with the top of the mounting base, a limiting spring sleeved on the probe main body is arranged between the limiting boss and the probe shaft cover, and the probe shaft cover is matched with the mounting base to movably limit the probe main body. The probe main body is fixed in the mounting base and cannot be pulled out under the limiting of the limiting boss; and the limiting boss is matched with the limiting spring to move up and down or rotate the probe main body to adjust the position, so that the bent and knotted optical fiber is arranged or the signal of the optical fiber probe is adjusted.

The invention relates to the technical field of feature extraction, and discloses a feature extraction method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a functional imaging video, and obtaining a target feature based on the functional imaging video and a trained feature extraction model, the feature extraction model comprises a feature extraction network, a feature compression filtering network and a feature output network which are connected in sequence, and finally registering the functional imaging video based on the target features. According to the method, feature extraction is carried out on the functional imaging video by adopting the feature extraction model of deep learning, then registration between frames is carried out on the functional imaging video by using the extracted features, the extracted features are more beneficial to registration and are less interfered by noise, and the anti-interference capability of the registration method is improved.

A diagnostic system for determining a health condition of an organ of a patient that has been administered a radioisotope dose uptaken by the organ, comprises at least one processor configured for receiving image data acquired from the patient when the radioisotope dose is active in the patient, analyzing the received image data to determine a functional organ volume index and an individual organ function index, staging a health of the organ based on the determined functional organ volume index and the determined individual organ function index. The diagnostic system further comprises a user interface device configured for communicating the staged health of the organ to a clinician.

The invention provides an azobenzothiazole compound and a preparation method thereof, a pharmaceutical composition and application thereof, and a nuclear medicine imaging agent, and belongs to the technical field of medicines. The azobenzothiazole compound provided by the invention has a structure as shown in a formula I. The azobenzothiazole compound provided by the invention has good affinity to the alpha-synuclein aggregate, and can be used for preparing a medicine for detecting the alpha-synuclein aggregate in a tissue sample. Meanwhile, a fluorine-18 marker obtained after the azobenzothiazole compound is labeled with radioisotope fluorine-18 can be used for nuclear medicine imaging, and the fluorine-18 marker can be used for functional imaging of intracerebral alpha-synuclein aggregates, such as intracerebral alpha-synuclein aggregates, intracerebral alpha-synuclein aggregates, intracerebral alpha-synuclein aggregates and intracerebral alpha-synuclein aggregates. The alpha-synuclein is suitable for being used as a radiodiagnosis medicine for cerebral neurodegenerative diseases or other related diseases taking the alpha-synuclein aggregate as a pathological marker. # imgabs0 #

The invention provides a multi-modal imaging system fusing physiological parameter monitoring, and the system comprises an ultrasonic collection module which collects ultrasonic detection signals according to a preset time sequence; the physiological acquisition module is used for acquiring time sequence reflecting physiological signals according to a preset time sequence; the feature fusion module is used for carrying out time registration on the ultrasonic detection signals and the time sequence physiological signals, extracting multi-modal features and fusing the multi-modal features to form a joint feature vector; the multi-modal estimation module is used for analyzing and obtaining an imaging result and multi-modal physiological parameters of the target tissue or blood vessel based on the joint feature vector; and the output module is used for outputting the imaging result and the multi-modal physiological parameters. According to the method, ultrasonic detection signals and various time sequence physiological signals are deeply fused, so that global accurate capture of vascular structures, dynamic characteristics and physiological time sequence information is realized, and a full-link closed loop of structural imaging, functional imaging and multi-parameter continuous monitoring is successfully cut through; and a high-precision, multi-dimensional and explainable solution is provided for cardiovascular risk assessment and individualized health management.

To provide an image-guided variable spot light stimulation electrophysiology device applicable to structural / functional imaging and evaluation.SOLUTION: To provide an application of a device for performing image-guided functional assessment based on variable spot light stimulation of a light-activated biological sample to determine changes in functional health during disease progression and treatment. More specifically, the invention relates to the application of the device in the diagnosis of vision and neurological disorders.SELECTED DRAWING: Figure 1

The utility model discloses a near-infrared brain function imaging probe frame which comprises a support and is characterized in that the support is square and is provided with a plurality of open holes, the support is fixedly connected with a connecting frame through a plurality of supporting rods, and the support and the connecting frame are elastic and can generate elastic deformation when making contact with the head of a patient so as to be attached to the curvature of the head. The four corners of the connecting frame are fixedly connected with extension arms respectively; the outer end of each extending arm is provided with a cross-shaped key groove and a set of evenly-distributed clamping grooves, the clamping grooves are distributed in a cross shape, and each clamping groove is formed in the included angle of the corresponding cross-shaped key groove. The utility model relates to the technical field of near-infrared brain function imaging supports, in particular to a near-infrared brain function imaging probe frame, the elastic design of the frame and a connecting frame enables the near-infrared brain function imaging probe frame to be attached to the curvature of the head of a patient, the imaging accuracy is improved, the design of a clamping block and a cross-shaped key groove enables a near-infrared brain function probe to be rapidly installed and fixed, and the structure is simple. And the use process is simplified.

The utility model provides an ultrasonic-photoacoustic composite laparoscope and an ultrasonic-photoacoustic imaging system. The ultrasound-photoacoustic composite laparoscope comprises an insertion part and a head end part, the head end part is connected to the far end of the insertion part, the ultrasound-photoacoustic composite laparoscope further comprises a light guide part, the light guide part is located outside the insertion part, and the far end of the light guide part is connected to the head end part. According to the ultrasonic-photoacoustic composite laparoscope, ultrasonic imaging, photoacoustic imaging and ultrasonic-photoacoustic imaging can be achieved, and therefore large-depth high-resolution, high-contrast and high-sensitivity structural imaging and functional imaging of an organizational body can be achieved, and the accuracy rate of in-vivo diagnosis is greatly improved. According to the ultrasound-photoacoustic composite laparoscope, the light guide part is externally connected to the insertion part, and the overall dimension of the insertion part can be smaller, so that the space utilization rate of the insertion part can be higher, and the effect of the ultrasound-photoacoustic composite laparoscope used for minimally invasive surgery is better.

The invention discloses a method for verifying LCBM tissue pathology types based on image parameter differences of DCE-MRI combined with DWI. By analyzing ADC values and DCE-MRI parameter differences of different pathological types of LCBMs and application values of DCE-MRI and DWI parameters in differential diagnosis of different histopathological LCBMs, contribution of ADC values and DCE-MRI parameters to different histopathological LCBMs is quantified by logistic regression, influences of DCE-MRI parameters on ADC values of different histopathological LCBMs are tested by multiple linear regression, the DCE-MRI parameters are tested by multiple linear regression, and the LCBMs of different histopathological LCBMs of different histopathological LCBMs of different pathological types are tested by multiple linear regression. The influence of ADC values on BBB leakage of the LCBM in different tissue pathologies not only verifies the characterization capability of multi-modal functional imaging parameters on the LCBM microenvironment, but also provides a new theoretical support and technical path for basic research and precise diagnosis and treatment of the LCBM through multi-modal integration, parameter weight quantification, interaction mechanism analysis and clinical application framework construction.

To provide an imaging apparatus having an image processing function.SOLUTION: An imaging device with an additional function such as image processing can hold analog data obtained by imaging operation in a pixel and take out data obtained by multiplying the analog data by a given weight coefficient. In the pixel, difference data between adjacent light-receiving devices can be obtained, and data on a luminance gradient can be obtained. When the information is taken into a neural network or the like, distance information or the like can be inferred. In addition, an enormous amount of image data can be retained in a pixel as analog data, so that processing can be performed efficiently.SELECTED DRAWING: Figure 1

Embodiments of the present application provide a head cap and a brain electrical near-infrared synchronous acquisition device. The head cap comprises a main body, a plurality of pads, a plurality of probe mounting portions and a plurality of electrode mounting portions. The main body is used to form a space for accommodating a head of a subject. The plurality of pads are arranged at different positions on the inner side of a first part of the main body, so that each pad forms a laminated structure with the first part of the main body. The plurality of probe mounting portions are arranged on the laminated structure and are used to mount probes for acquiring fNIRS signals. The plurality of electrode mounting portions are arranged on a second part of the main body which is not provided with the plurality of pads, and are used to mount electrodes for acquiring electroencephalogram signals. In this way, the pads can position the probe mounting portions and maintain the spacing between the probe mounting portions, thereby improving the performance of near-infrared brain function imaging. Meanwhile, the electrodes for electroencephalogram and the probes for near-infrared brain function imaging do not interfere with each other, are reasonably arranged, and achieve the best data acquisition effect.

The invention belongs to the technical field of brain function network modeling and fMRI data analysis, and discloses a multi-task brain function network modeling method based on an L2 regularization convolution encoder. According to the method, a full convolution architecture is adopted, limitation of a full connection layer is avoided, fMRI data of different lengths are self-adapted, and cross-task universal feature learning is realized; and in combination with the time and channel attention mechanism of L2 regularization, the model characterization capability is enhanced, and the over-fitting risk is reduced. And through a Pearson's correlation coefficient, a space overlapping ratio and a genetic similarity ratio, a task-related function network and a resting state brain network are automatically identified, and the hierarchical organization of the brain function network is disclosed. According to the method, the accuracy and stability of fMRI data analysis can be improved, brain disease diagnosis, neuroscience research and personalized medical treatment are assisted, compared with a traditional method, the method has higher interpretability and robustness, and the efficiency of brain function image analysis is improved.