174 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.

The invention relates to the technical field of brain function imaging, in particular to a target crowd recognition method and device based on neural blood flow feature multi-level fusion, and the method comprises the steps: collecting brain nerve blood flow signals of normal and target crowds by using synchronous EEG-fNIRS equipment, preprocessing and extracting single-mode features, and obtaining a single-mode feature set; a multi-frequency local nerve and blood vessel coupling analysis method is used for calculating nerve and blood vessel coupling strength characteristics, a space co-positioning method is used for unifying nerve and blood flow modal space information, the position precision is improved, and data layer fusion is achieved; and integrating and analyzing different modal feature space relationships by using a Yeo7 brain template to realize feature layer fusion, and finally training various machine learning classifiers by using significant difference features to realize identification of a target population. Therefore, the problems that in the prior art, macroscopic signal correlation is paid more attention to, so that analysis of the synergistic effect of cross-modal space information in a specific brain region is deficient, and deep understanding of a neurovascular function mechanism and brain region role revelation are restricted are solved.

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.

The present invention relates to a highly functional imaging device that can be manufactured through a small number of steps. The imaging device is formed in such a manner that a first stacked body in which a plurality of devices are stacked and a second stacked body in which a plurality of devices are stacked are bonded to each other. For example, a pixel circuit, a driver circuit of a pixel, and the like can be provided in the first stacked body, and a reading circuit of the pixel circuit, a memory circuit, a driver circuit of the memory circuit, and the like can be provided in the second stacked body. With these structures, the imaging device which is small can be formed. Furthermore, wiring delay or the like can be prevented by stacking circuits, so that high-speed operation can be performed.

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.

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 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 the technical field of cranial nerve regulation and control, and discloses a dynamic closed-loop nerve regulation and control method integrating an ultrasonic array element and an fNIRS probe, which adopts a mode of combining a near-infrared light detector and the ultrasonic array element, can utilize the characteristics of transcranial focused ultrasound to stimulate deep nuclei of the brain, and utilizes near-infrared to observe the change of cerebral cortex in real time. Real-time observation of brain blood oxygen level change caused by cortical excitability of each brain region of a brain function network is realized, closed-loop feedback is formed, then dynamic parameter adjustment is performed on the phased array ultrasonic array, dynamic closed-loop nerve regulation and control of the integrated ultrasonic array element and the near-infrared brain function imaging probe are realized, and the brain blood oxygen level change is observed in real time. And the maximum change of the cortex excitability of the expected brain region or the brain network node is obtained through the focusing process, so that the precision of the stimulation target region is realized.

The utility model provides a transcranial magnetic stimulation and near-infrared brain function imaging detection integrated device. The transcranial magnetic stimulation and near-infrared brain function imaging detection integrated device comprises a transcranial magnetic stimulation coil and a probe mounting seat, the transcranial magnetic stimulation coil comprises a plurality of coil bodies, and the paired coil bodies are matched to form a V-shaped structure on the sides facing the head of a user. The probe mounting seat is arranged on the side, facing the head of a user, of the coil body, a plurality of mounting holes are formed in the probe mounting seat and used for mounting near-infrared probes, and the near-infrared probes are used for transmitting or receiving near-infrared light to the head of the user. By means of the structure, stimulation focusing can be achieved, the stimulation depth can be increased, the treatment effect can be improved, the detection area of the near-infrared probe installed on the probe installation base can cover the treatment area of transcranial magnetic stimulation more, the coil body of the V-shaped structure enables the near-infrared probe to be attached to the head of a user, and therefore the treatment effect of transcranial magnetic stimulation is improved. The detection effect of the near-infrared probe is effectively improved, and the overall structure is more reasonable and compact.

The invention provides a swallowing function evaluation system and method based on multi-modal fusion, equipment and a medium. A swallowing radiography device, a multi-channel array flexible myoelectricity acquisition sensor and a near-infrared brain function imaging device of the system are respectively used for synchronously acquiring swallowing image information, swallowing muscle group myoelectricity array information and near-infrared brain function imaging information when a patient executes a swallowing mode; and the main controller processes the synchronously acquired information to realize swallowing function evaluation. According to the method, sEMG array image information of sEMG and near-infrared brain function imaging information are combined with swallowing image information to construct a human body swallowing evaluation model, and a self-developed multi-channel array flexible myoelectricity acquisition sensor is adopted to construct a correlation mapping model from a swallowing contrast internal structure to external muscle point information; and by utilizing the priori of the myoelectricity information and the near-infrared brain imaging information, the evaluation and prediction of the dysphagia are realized by adopting a classifier algorithm, and technical support is provided for the application of the near-infrared technology in the swallowing evaluation.

The invention discloses a human body gait recognition method and device based on multi-modal fusion, and belongs to the field of human body gait assessment, and the method comprises the steps: collecting electromyographic signals of muscles at different movement positions of lower limbs; collecting near-infrared brain function imaging data of the brain in a gait image and an idle state; collecting pressure information of the planta pedis in the movement process; the electromyographic signals, the near-infrared brain function imaging data and the plantar pressure information are input into a multi-modal fusion model, feature extraction is conducted on the electromyographic signals, the near-infrared brain function imaging data and the plantar pressure information, and different features are fused through a cross attention mechanism; the classification algorithm identifies the fused features and performs gait evaluation, and as the electromyographic signals, the pressure information of the planta pedis and the near-infrared brain function imaging data are synchronously generated with the human body movement, the human body gait identified through the data is low in hysteresis quality and high in accuracy.

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 utility model discloses a transcranial magnetic stimulation and near-infrared brain function acquisition synchronization system. The system comprises a visual stimulation issuing device, a transcranial magnetic stimulation issuing device, a transcranial magnetic stimulation coil racket, a near-infrared brain function imaging acquisition device and an acquisition optical fiber. The visual stimulation issuing device is respectively connected with the near-infrared brain function imaging acquisition device and the transcranial magnetic stimulation issuing device; the near-infrared brain function imaging acquisition equipment is connected with one end of the acquisition optical fiber, and the other end of the acquisition optical fiber is connected with a scalp target; the transcranial magnetic stimulation issuing device is connected with the transcranial magnetic stimulation coil racket. According to the utility model, the transcranial magnetic stimulation can be carried out on a patient, and the synchronous marking of the visual prompt time point can be carried out on the acquired near-infrared signal by the near-infrared brain function imaging acquisition equipment, so that the delay error caused by the manual marking of the visual prompt time point can be avoided.

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 #