10 results about "Central gray matter" patented technology

The invention discloses a method, device and equipment for generating a head model, a storage medium and a program product. The method is characterized by comprising the following steps of: receiving and verifying original three-dimensional T1 weighted image data and an original three-dimensional grid model; performing tissue segmentation based on the verified three-dimensional T1 weighted image data and the original three-dimensional T1 weighted image data to obtain a cerebral grey matter mask, a cerebral white matter mask, a scalp mask and a skull mask; performing topological structure repair on the brain grey matter mask and the brain white matter mask to obtain a brain mask; respectively converting the scalp mask, the skull mask and the brain mask into a scalp mesh model, a skull mesh model and a brain mesh model; calculating and applying a spatial transformation matrix from the verified three-dimensional grid model to the scalp grid model, and performing spatial registration and fusion on the scalp grid model, the skull grid model and the brain grid model to obtain a head model; the method has the advantages that the efficiency, precision and robustness of head model generation are effectively improved, and the method has good cross-platform deployment capability.

The invention discloses a multi-mode brain dysfunction auxiliary diagnosis method based on a dynamic function connection network. A two-stage collaborative learning framework from an individual brain graph to a group relation graph is constructed. Firstly, an individual multi-modal fusion brain map is constructed, node features of the individual multi-modal fusion brain map are obtained through node regularization regression analysis of an rs-fMRI time sequence, an adjacent matrix is obtained through calculation of the brain interval grey matter volume difference of a T1 image, and individual enhancement characterization is obtained through map convolutional network fusion. And then constructing a group relationship enhancement graph, taking individual representation as node features, constructing a dual-channel adjacency relationship for distinguishing homologous / heterologous connection according to age and gender, obtaining final discriminative representation through dual-channel graph attention network aggregation, and performing classification diagnosis according to the final discriminative representation. According to the method, deep fusion of multi-modal information and explicit modeling of key biological variables are realized, and an effective tool is provided for accurate and explainable auxiliary diagnosis of brain diseases.

The invention discloses a cerebral cortex penetrator small blood vessel magnetic resonance imaging method based on an inflow enhancement effect. The method comprises the following steps: modeling a penetrator small blood vessel to generate a blood vessel TOF (Time of Flight) image; calculating the blood vessel-grey matter contrast ratio of the blood vessel TOF image under different FAs and different TRs, and optimizing the FAs and the TRs according to the blood vessel-tissue contrast ratio; obtaining a structural image of the in-vivo brain tissue, performing cortex reconstruction, and calculating an angle of a surface normal of each cortex vertex relative to the B0 field to obtain a cortex angle graph; adjusting a single-layer blood vessel scanning plane angle according to the cortex angle diagram; and according to the optimized FA and TR and the single-layer blood vessel scanning plane angle determined in the step S4, carrying out magnetic resonance imaging on the cerebral cortex perforation small blood vessel. The invention further discloses a cerebral cortex puncturing small blood vessel magnetic resonance imaging device based on the inflow enhancement effect. According to the method and the device, magnetic resonance imaging of the cerebral cortex perforation small blood vessel can be realized under the non-invasive and contrast-agent-free conditions.

The application discloses a kind of whole brain segmentation method, system, equipment and medium, method includes obtaining CT image data, and standard image data is obtained by preprocessing;Standard image data is input into whole brain segmentation model, and whole brain segmentation result is obtained.Wherein, whole brain segmentation model is obtained based on sample annotation data training, and whole brain segmentation model includes CNN encoder, Transformer encoder, multiple cross-domain fusion modules and the feature enhancement module corresponding to cross-domain fusion module one by one, and decoder.The application has the advantages that the soft tissue contrast of CT image data is low, it is difficult to distinguish cerebral grey matter, cerebral white matter, cerebrospinal fluid and brainstem brain tissue problem, by CNN encoder extraction local feature and Transformer encoder extraction global semantic feature, and local feature and global semantic feature dynamic interaction and fusion, accurately segmented advantage is carried out to whole brain cerebral grey matter, cerebral white matter, cerebrospinal fluid and brainstem brain tissue.

The invention relates to the technical field of virtual reality, in particular to a virtual reality-combined neurosurgery preoperative simulation training method, which comprises the following steps of: acquiring a grey matter boundary and analyzing a nerve fiber trend, delimiting a path to form a training path, screening out a path range in contact with a functional area, loading track comparison and extracting an overlapping path, and performing simulation training on the overlapping path. Identifying the corresponding relation between the path abnormity and the area, and recombining the action sequence and the execution range according to the problem distribution. According to the invention, by identifying the spatial continuity of nodes in an image, combining the contact condition of a path and a functional region, screening a response region which can be included, comparing the spatial correspondence between an operation track and the nodes, mining offset and fracture points in the path, and determining the spatial continuity of the nodes. The action sequence is rearranged according to the frequent occurrence positions of the actions in the path and the continuation relation of the nodes, so that the training path has continuity and fluency, the action connection between the regions is optimized, and the coordination and consistency of the path and the operation content are improved.

The present application relates to neuromodulation and brain-computer interface technical field, propose a kind of robust optimization method and system under the condition of parameter uncertainty, robust optimization method includes constructing five-layer head tissue model including skin, skull, cerebrospinal fluid, grey matter and white matter based on the magnetic resonance image of patient, and the independent conductivity uncertainty radius of each layer of tissue is set, multi-dimensional ellipsoid uncertainty set is constructed;Min-Max worst case cost function is constructed and is solved, guarantee in ellipsoid set under the worst case, electrode current weight meets safety constraint;Worst case cost function is converted into second-order cone programming form using dual principle;Pseudo-trace perception sliding window mechanism is introduced to monitor the continuity of physiological signal or impedance data, when detecting non-physiological mutation, trigger re-optimization by calling historical stable parameters and amplifying uncertainty radius;When re-optimization has no solution, trigger safety derating mechanism, and the current instruction of previous period is scaled proportionally.

The invention discloses an oxygen uptake cardiopulmonary endurance testing method based on load turn-back walking and a human brain structure, and relates to the technical field of exercise physiology and biomedicine detection.The method comprises the steps that progressive load turn-back walking exercise data and a high-resolution brain structure image of a subject are obtained; extracting key brain region parameters such as the thickness of the anterior cinerary cortex, the grey matter density of island leaves and the signal intensity of brainstem respiratory center; normalizing the motion features and brain structure parameters and then constructing a 12-dimensional multi-modal fusion feature vector; and inputting a deep feedforward neural network model to predict the maximum oxygen uptake, and performing five-level cardiopulmonary endurance evaluation according to an age and gender correction result. According to the method, quantitative association between peripheral exercise performance and a central nervous anatomy basis can be realized, the heart and lung endurance evaluation precision of old people and individuals with abnormal neurological functions is remarkably improved, and rapid screening and personalized exercise prescription making are supported.

The application provides a grey / white matter partitioned biomimetic spinal cord scaffold which can be customized grey / white matter partitioned and can match the grey / white matter morphology of any segment; the grey / white matter partitioned biomimetic spinal cord scaffold is composed of an internal 'butterfly' shaped grey matter area and an external white matter area, and the whole appearance is in a cylindrical shape; the grey matter area mainly comprises a hydrogel material; the white matter area mainly comprises a hydrogel and a directional fiber material; the direction of the directional fiber material is consistent with the longitudinal direction of the scaffold; the grey matter area and the white matter area are fused into a whole through the hydrogel, and there is no obvious barrier structure between the grey matter area and the white matter area.

A device or system for delivering fluid to or removing fluid from a CSF-containing space of a brain and for recording electrical activity from white or grey matter in the brain includes a catheter including a proximal end, a distal end portion, a first lumen extending from the proximal end to the distal end portion, and one or more electrodes positioned relative to the catheter a distance from a distal end of the catheter, such that the one or more electrodes would be placed in contact with white or grey matter of the brain if the distal end of the catheter were positioned in the CSF-containing space. The catheter may include the electrodes or a lead adjacent the catheter may include the electrodes.

A computer-implemented method for parceling grey matter of a human brain of a human patient comprising obtaining a tractogram including tractogram streamlines, each having a first extremity located in a first portion of grey matter of a second extremity located in a second portion of grey matter. The parceling method also comprises using a predetermined clustering algorithm to obtain tractogram streamline clusters, and, for each cluster of at least a part of the clusters, identifying a respective first region of grey matter including for each streamline of the cluster its first extremity, and a respective second region of grey matter including for each streamline of the cluster its second extremity. The parceling method also comprises determining a parcellation based on the identified regions, including an iterative merging process which includes merging pairs of regions based on a metric quantifying an overlap.