60 results about "White matter" patented technology

The invention relates to the technical field of medical care informatics, and discloses an intelligent post-stroke cognitive impairment assessment method based on brain network dynamic reconstruction, which comprises the following steps: acquiring multi-modal brain image data of a patient, dynamically compensating the difference between haemodynamic delay and white matter conduction velocity through a nerve-blood vessel coupling model, and calculating the post-stroke cognitive impairment; precise space-time alignment of function and structure signals is realized; a pulse neural network dynamic entropy change model is constructed based on the alignment data, functional connection strength change is coded into a pulse distribution sequence, and Gamma wave band synchronization enhancement and other compensatory features are extracted; constraining rationality of brain network reconstruction by adopting an energy optimal transmission model, and generating a compensatory thermodynamic diagram; and real-time calculation of the edge end is realized through pulse time sequence compression coding. The limitation of traditional static analysis is avoided, the algorithm achieves microsecond response on embedded equipment through the pulse coding technology, and a reliable stroke rehabilitation evaluation tool is provided for primary hospitals.

The invention relates to a fetal brain tissue segmentation method based on prior information guidance, and the method comprises the following steps: obtaining a public data set, and selecting a part of data in the public data set as a training set; preprocessing the training set to obtain a grey-white matter volume ratio, an edge feature map and a gestational week feature map; constructing a prior segmentation model GA-Swin, and designing a loss function LTotal to train the model; and finally obtaining a trained fetal brain segmentation model. According to the method, on the basis of following the development law, each tissue of the fetal brain can be precisely segmented, and collaborative optimization of precision interpretability and biological rationality in medical image analysis is achieved.

The invention discloses a brain-computer interface signal enhancement and evaluation method fusing physical information. The method comprises the following steps: firstly, based on an individual structure magnetic resonance image, constructing a personalized six-layer brain tissue anatomical model comprising a cortex, a white matter, cerebrospinal fluid, a dura mater, a skull and a scalp, and endowing differentiated conductivity parameters; secondly, neuroelectrophysiology priori knowledge such as neurodynamics and white matter anisotropic conduction is converted into a representation rule which can be learned by a neural network; then, the rules are systematically embedded into a physical information neural network in a differentiable physical constraint form, including a cortical neurodynamic equation residual error, a volume conduction equation residual error of each layer and an interlayer interface continuity constraint; and finally, training a network by using the scalp electroencephalogram signals, and jointly outputting high-fidelity intracranial electroencephalogram signals and multi-modal neurophysiological information by minimizing a loss function containing reconstruction and physical constraints. According to the method, the fidelity, the physical rationality and the clinical interpretability of signal enhancement are effectively improved.

The invention relates to the technical field of multi-modal registration, in particular to a neurosurgery visual operation navigation system based on multi-modal fusion, which comprises a feature fusion module, an image correction module, a deformation correction module, a layer labeling module and a navigation interaction module. According to the method, a DTI image and a CT image are aligned through three-dimensional pairing, white matter fiber and temporal bone edge directions are extracted, feature integrity is enhanced, edges are corrected through a structural similarity algorithm, space mapping precision is improved, a blood vessel center line and an ultrasonic image edge point track are combined, deformation is corrected, and drift and artifacts in an operation are restrained; the structure continuity of the blood vessel and the fiber is guaranteed, the positions of the white matter fiber and the blood vessel are integrated, a consistent directional diagram layer is formed, the navigation response sensitivity is improved through three-dimensional distance evaluation, a self-matching adjustment mechanism is set, the feature fusion and correction precision is enhanced, image deviation interference is reduced, and the navigation real-time performance and the analytic performance are improved.

The invention discloses a method for determining an OAB target based on brain network characteristics. The method comprises the following steps: a) detecting the functional connection strength of the right forehead cortex of a patient in a resting state through functional magnetic resonance imaging; b) identifying significantly weakened brain region connections, including paracentral lobules, cerebellar lower feet and marginal systems, as compared to a healthy control group; c) determining the number of white matter fiber bundles with abnormal structural connection in the brain interval by combining a diffusion tensor imaging fiber tracking technology; and d) selecting a brain region with abnormal function and structure connection as a nerve regulation treatment target.

The invention relates to the technical field of medical treatment, and particularly discloses a training method for delaying development of Alzheimer's disease, which comprises the following steps: (a) a neural pathway activation stage: generating a dynamic three-dimensional space navigation task through a virtual reality system and displaying a color coding path to a patient; the method comprises the following steps: (c) a lymphatic driving stage: starting a 40Hz multi-mode stimulation combination after metabolic regulation reaches the standard, and (d) a closed-loop optimization stage: detecting saliva exosome A beta 42 concentration or EEG gamma wave power every two weeks, each time is 40 minutes every day, and the steps (a)-(b)-(c) are executed in sequence; neuropathology is improved, compared with the prior art, the hippocampus atrophy rate is remarkably reduced, the A beta 42 pathological deposition removal efficiency is high, and the white matter fiber integrity is improved; the cognitive function of the patient is enhanced, the space navigation capability is optimized, and the attention and work memory are improved.

The invention provides an auxiliary analysis method, device and equipment for a neural circuit injury position and a medium, and relates to the field of medical image processing, and the method comprises the steps: obtaining whole brain sample data, including fMRI data and DTI data of a healthy sample and a tested sample; selecting a seed point based on the fMRI data, establishing whole brain function connection based on the seed point, and extracting a time-varying connection coefficient sequence between the seed point and the region of interest; based on the DTI data, determining a connection fiber between the seed point and the region of interest through probabilistic fiber tracking, obtaining a target liposome representing the connection fiber and a surrounding region thereof, and obtaining a white matter bold signal sequence of the target liposome; and performing difference analysis on the connection coefficient sequence and the white matter bold signal sequence of the healthy sample and the tested sample to obtain the abnormal voxel of the tested sample, and determining the neural circuit injury position according to the coordinate of the abnormal voxel, thereby providing important information for the research of neural activity.

The present application relates to reducing the adverse effects of oligodendrocyte loss, astrocyte loss, or white matter loss, including age-related oligodendrocyte loss, astrocyte loss, or white matter loss, in the brain of a subject. The present application also relates to rejuvenating glial progenitor cells or their progeny, or enhancing the developmental potential of glial progenitor cells or their progeny.

The application carries out quantitative susceptibility mapping (QSM) reconstruction on original gradient echo data (GRE), then constructs an individual space standardization QSM brain template by using structural images, carries out linear and nonlinear registration processing on QSM images of all subjects and the brain template, so as to achieve the purpose of standardization processing of the QSM images; meanwhile, the structural images are automatically segmented, the gray matter and white matter masks obtained after segmentation are used to carry out matrix point multiplication on the QSM images, then the standardized QSM images are smoothed and corresponding smoothing compensation is carried out; in FSL, a general linear model is constructed, and voxel-level whole brain statistical analysis is carried out on the QSM images; the masks obtained after automatic nucleus segmentation are used to extract the susceptibility values of corresponding deep nuclei in the QSM images; the whole process does not need to manually draw the interested region, and the quantitative analysis of the susceptibility values based on voxels and based on the interested region can be automatically completed, and the repeatability, comparability and reliability are greatly improved.

The application relates to a mild cognitive impairment development process prediction method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring first diffusion tensor imaging images of a mild cognitive impairment patient in multiple follow-ups; processing each first diffusion tensor imaging image, extracting white matter fibers between all hippocampal voxels and other brain voxels; performing regional segmentation on the hippocampus according to the white matter fibers between all hippocampal voxels and other brain voxels, and constructing hippocampal subregions; constructing a first gradient change feature of the white matter fibers of each hippocampal subregion according to the gradient change of the target feature of the white matter fibers of the hippocampal subregion; and predicting the cognitive impairment development process of the measured object according to the basic information, clinical information and first gradient change feature of the white matter fibers of the hippocampal subregion of the patient. The method can improve disease classification accuracy and specificity, and can predict the cognitive impairment development process of the measured object.

The invention relates to an MRI image-based early-stage paraphrase softening risk prediction method and an MRI image-based early-stage paraphrase softening risk prediction system. The method comprises the following steps: acquiring a clinical MRI image and a clinical medical history of a to-be-predicted risk patient; preprocessing the clinical MRI image to obtain a to-be-detected MRI image; and inputting a to-be-detected MRI image and the clinical medical history into the ventricular paraphrine softening prediction model to obtain a ventricular paraphrine softening risk prediction result. By adopting the method, the disease risk of the child patient can be reflected more comprehensively through the risk prediction result, and more accurate support is provided for clinical decision making.

The present invention discloses a method for individual structural target localization of transcranial magnetic stimulation based on diffusion-weighted imaging. The present invention adopts a precise localization method for individual structures of transcranial magnetic stimulation based on diffusion-weighted imaging, which can not only solve the limitation that conventional TMS cannot have a specific effect on deep nuclei, but also transmit electrical stimulation from the superficial cortex of the brain to deep nuclei through white matter structural connections in a non-invasive manner, avoiding the adverse risks existing in traditional deep brain electrical stimulation. At the same time, when providing an individualized stimulation target plan for patients, this method uses a white matter structural connection index that is more stable than the functional connection strength calculated by resting-state functional magnetic resonance, providing a precise intervention guidance plan that is more stable and reliable in time and has neuroanatomical significance while solving the problem of strong individual heterogeneity in patients with mental disorders.

The invention provides a human brain superficial layer white matter fiber structure map construction method and system, and the method comprises the steps: generating a finely divided whole brain function fiber cluster map in an unsupervised manner based on whole brain diffusion magnetic resonance imaging data; in combination with a geometric feature threshold value and a deep learning classifier, identifying superficial layer white matter fibers from the whole brain function fiber cluster and carrying out hierarchical clustering to generate a superficial layer white matter fiber sub-atlas with the optimal clustering number; and analyzing the functional attributes of the superficial layer white matter fibers through a trajectory weighted dynamic functional connection analysis method to obtain a superficial layer white matter fiber structure chart of the human brain. According to the method, the technical blank in the field is filled, and a high-quality data acquisition channel is provided for research based on superficial layer white matter.

The present invention pertains to the anti-inflammatory therapeutic effect of xantohumol in spinal cord injury (SCI). The continuous administration of xanthohumol for 1-8 weeks to SCI rats resulted in improved results in 4 clinical tests used and in lowering and faster elimination of macrophages from the SCI lesion. Since the infiltration of the SCI lesion by numerous phagocytic macrophages indicates a severe destructive inflammation of extraordinary longevity, administration of xanthohumol is neuroprotective and resulted in a better and faster recovery of the locomotor function and the strength and sensory function in the hind limbs, in a shorter period of paralysis of the urinary bladder and in the recovery of the body weight lost due to the SCI surgery. Since the traumatic brain injury (TBI) involving the white matter, and stroke involving the white matter initiate the severe destructive inflammation as in the SCI, the administration of xanthohumol is expected to be anti-inflammatory and neuroprotective in both brain diseases. Since neurodegenerative diseases including Alzheimer's disease, frontotemporal dementia and Parkinson's disease, immune mediated neuroinflammation including multiple sclerosis and neuromyelitis optica and cerebrospinal infections have inflammatory pathogenesis involving microgliosis and infiltration by macrophages, the administration of xanthohumol is expected to result in therapeutic inhibition of progression of all above diseases as well as of related neurodegenerative, immune mediated and infectious diseases of the brain and of the spinal cord.

A computer-implemented method for adjustable three-dimensional (3D) rendering of locations in a subject includes a step of receiving image data having a discrete spatial resolution for white matter tracts in a subject where the image data is generated by magnetic diffusion imaging. A first stereoscopic image is rendered on a display from the image data. The first stereoscopic image includes image parallax, which allows three-dimensional viewing. An input is received from a pointing device or a hand gesture that enables manipulation of the first stereoscopic image while maintaining proper three-dimensional spatial relationships. The pointing device interacts with the first stereoscopic image in three-dimensional space with six degrees of freedom.

The invention discloses application of steroid saponin of trillium tschonoskii maxim to preparation of a medicine for treating vascular dementia, and relates to the technical field of medicines. Animal experiments prove that the berberis apiacea steroid saponin can improve the spatial reference learning function of cerebral ischemia rats, improve the spatial reference memory function of the cerebral ischemia rats and enhance the long-term memory function of the cerebral ischemia rats. In addition, brain tissue damage and white matter structure damage of rats suffering from cerebral ischemia can be relieved, axonal myelin sheath microstructure reconstruction and white matter fiber reconstruction of the rats suffering from cerebral ischemia are promoted, and myelin sheath regeneration of rats suffering from vascular dementia is promoted. Network pharmacological analysis finds that the age grass total steroid saponin has a wide regulation effect on OPCs and OLs cell components and molecular functions, and further, OPCs differentiation myelin sheath inhibition related factors are regulated and controlled, and white matter myelin sheath regeneration is promoted.

A nutritional composition for promoting brain development. The nutritional composition comprises the following essential components: docosahexaenoic acid, arachidonic acid, galactooligosaccharide, 1,3-dioleoyl-2-palmitoyl triglyceride, lutein, nucleotides, lactoferrin, and casein phosphopeptides. The nutritional composition and food containing same can effectively promote brain structure development and neural network formation. Specifically, on the brain structure, the brain weight can be particularly increased, and the maturation of the white matter region is promoted, and the beneficial development of lipid composition in the brain can also be promoted. Furthermore, in the neural network formation, related protein expression of neural network key components such as synapses and myelin sheaths can be promoted, thereby facilitating nerve cell activity and neural signal transmission, and further facilitating cognitive and neurobehavioral development.

This invention discloses a magnetic resonance imaging (MRI) method for evaluating the therapeutic effect of cerebral palsy rehabilitation in children, relating to the field of medical image processing technology. The method includes: acquiring structural imaging data (T1-weighted imaging and diffusion tensor imaging) and resting-state imaging data for each child patient; extracting brain and tissue boundaries from T1-weighted imaging using a 3D-Unet segmentation model; preprocessing the resting-state and structural imaging data and aligning them to brain boundaries, then registering these data to a standard brain template for children; acquiring and normalizing multiple clinical indicators based on the standard brain template, splicing them into multi-index vector data, inputting them into a pre-trained support vector machine model, and outputting differences in clinical indicators; determining abnormal brain regions for each child based on the differences, and finally generating a multimodal fusion index analysis report to observe changes in brain function and white matter integrity before and after rehabilitation.

A method for determining the degree of a central nervous system (CNS)-specific neurological condition in a subject includes collecting a biological sample of a biofluid from the subject and measuring the amount of a first biomarker, a metabolite of the first biomarker, or mRNA corresponding to the first biomarker from the sample via a dried spot or a microfluidic device. The biofluid is capillary blood or saliva, which offers the advantage of easy collection, making it attractive for field, hospital, and home environments. The method is useful in the diagnosis, care, and management of brain-specific abnormal neurological conditions in general, and specifically for traumatic brain injury (TBI), and (TBI-induced) Alzheimer's disease (AD) and Alexander disease (in which GFAP mutations are involved in white matter deterioration).

This application relates to the field of medical neuroimaging processing and computer-aided diagnosis technology, and discloses a method based on normal white matter. 18 An Alzheimer's Disease (AD) Auxiliary Assessment System Based on F-florbetapir Retention Features. This system includes a data acquisition module for acquiring multimodal brain imaging data of subjects; an image preprocessing and segmentation module for impurity removal and target localization of the image data; a feature extraction module for extracting image features from the processed images; and a joint assessment and prediction module for AD auxiliary assessment based on the extracted features, incorporating a subject performance characteristic model and a logistic regression system. This Alzheimer's Disease (AD) auxiliary assessment system can significantly improve the accuracy of early AD diagnosis, accurately predict the rate of cognitive decline, and dynamically monitor the effect of immunotherapy.

The invention relates to a transcranial ultrasonic nerve regulation and control device and a control method. The transcranial ultrasonic nerve regulation and control device comprises an ultrasonic generation unit, ultrasonic waves are controllably provided to an intracranial target area, and the ultrasonic generation unit is configured to provide the ultrasonic waves with the frequency ranging from 3.0 MHz to 8.0 MHz to the intracranial target area. According to the transcranial ultrasonic nerve regulation device and the control method, the intracranial nerves are stimulated through the high-frequency ultrasonic waves with the working frequency of 3.0-8.0 MHz, the transcranial ultrasonic nerve regulation device and the control method have remarkable advantages in cortex regulation, energy is more easily absorbed by superficial tissue, the stimulated area covers the cerebral cortex and superficial white matter, and interference of a non-targeted deep structure is avoided. Meanwhile, the spatial resolution of the ultrasound of the frequency band can reach the submillimeter level, the ultrasound can be accurately focused on a tiny functional subregion, and the ultrasound is particularly suitable for nerve regulation scenes needing accurate positioning intervention and is suitable for nerve regulation of focal epilepsy, chronic pain syndromes, visual and auditory cortex dysfunction and mental and psychological disorders.

The present invention relates to a method and a system for the segmentation of white matter hyperintensities (WMHs) present in magnetic resonance brain images, comprising: providing an array of trained convolutional neural networks (CNNs) with a magnetic resonance brain image; determining, for each of the CNNs and for each voxel, the probability that the given voxel corresponds to a pathological hyperintensity; calculating the average of all the probabilities determined for each voxel; comparing the averaged probabilities for each voxel with a threshold; generating an image mask with the voxels that exceed the threshold.

This disclosure relates to a flexible electrode for the spinal cord and a method for manufacturing the same. A flexible electrode for the spinal cord is provided, comprising: an attachment portion configured to be able to be placed on the white matter lateral to the epidural space or intradural space, and configured to acquire or apply electrical signals to the surface of the spinal cord; wherein the attachment portion of the flexible electrode includes a first insulating layer and a second insulating layer, and a conductive layer located between the first insulating layer and the second insulating layer; wherein the attachment portion of the flexible electrode further includes one or more electrode sites, each electrode site being electrically coupled to one of the conductive wires in the conductive layer, and contacting the spinal cord after implantation of the flexible electrode to acquire electrical signals from spinal nerves and transmit the acquired electrical signals through the conductive wires, or to apply electrical signals received through the conductive wires to spinal nerves.

The invention provides an autism spectrum disorder identification method and system based on image generation, equipment and a medium, which can synthesize an FA image from a conventional MRI image without increasing scanning time or replacing an imaging protocol, extract a quantitative index reflecting white matter development difference, and identify the autism spectrum disorder. And accurate distinguishing between the autism spectrum disorder and the comprehensive development retardation is realized. According to the method, DT I scanning with high time cost is avoided, the method is particularly suitable for children who are not easy to cooperate, the generated image has good anatomical consistency and biological interpretation, and doctors are helped to understand and collect information. Compared with an existing multi-mode or EEG method, the method is simple in structure, stable in recognition process, wide in application range and capable of being rapidly deployed on conventional image equipment, and the efficiency and accessibility of autism early screening and auxiliary diagnosis are remarkably improved.

The invention discloses a CSVD cognitive impairment prediction method and a CSVD cognitive impairment prediction system based on Transform and domain self-adaptive T2-FLAIR white matter high-signal radiomics characteristics, and belongs to the technical field of medical image processing and auxiliary evaluation. The system comprises a radiomics feature extraction module, a Transform prediction model module, a domain adaptive training module and an interpretability module. According to the method, image omics features of a white matter high-signal area in a T2-FLAIR image are extracted through a full-automatic process, a context relation between the features is modeled through a Transform architecture, the multi-center data generalization ability is improved in combination with a domain self-adaptive mechanism, feature importance visualization is achieved through Grad-CAM, and the method is used for assisting in predicting cognitive disorder risks and related scores of CSVD patients. According to the method, the problems of strong subjectivity, weak generalization ability, poor interpretability and the like in the prior art are solved, and an efficient tool is provided for early risk assessment of CSVD related cognitive impairment.

The invention relates to the technical field of biology, in particular to a medicine and application thereof. The drug is an exosome (DPSCs-Exos) derived from dental pulp stem cells (DPSCs-Exos). The DPSCs-Exos is given after acute cerebral apoplexy, so that sensory movement and cognitive function recovery after cerebral ischemia can be promoted. The DPSCs-Exos can improve ischemia for 45 minutes, and brain tissue injury and neurological function injury of animals after reperfusion for 28 days. The DPSCs-Exos promotes the expression increase of protein arginine methyltransferase (PRMT5) in oligodendroglia precursor cells (OPC), inhibits the expression of a differentiation inhibition factor 2 (ID2) through nucleation, promotes the OPCs to proliferate and differentiate into oligodendroglia cells (OL), and promotes the integrity repair of white matter. In addition, DPSCs-Exos can promote proliferation and migration of vascular endothelial cells and promote blood brain barrier repair.

Systems and methods for treating neurodegenerative disorders with high frequency stimulation are disclosed. A representative method for treating a patient includes applying an electrical signal to the patient via a treatment system that includes a signal delivery element positioned at or within a white matter of the patient's brain, spinal cord, or both, the electrical signal having a frequency of from about 1.5 kHz to about 100 kHz.

The present invention provides a method and apparatus for processing neuroimaging data. The method includes: obtaining a subcortical structural partition corresponding to the brain structural imaging data based on the brain structural imaging data and a brain structure segmentation model; obtaining a level set corresponding to the brain structural imaging data based on the brain structural imaging data, the white matter partition part included in the subcortical structural partition corresponding to the brain structural imaging data, and a cerebral cortex reconstruction model, and reconstructing a cerebral cortex image based on the level set corresponding to the brain structural imaging data to obtain reconstructed cerebral cortex imaging data; performing spherical registration between the surface of the cerebral cortex corresponding to the reconstructed cerebral cortex imaging data of the brain structural imaging data and the surface of the cerebral cortex in the first standard space based on a cerebral cortex registration model to obtain a spherical surface after registration of the surface of the cerebral cortex corresponding to the brain structural imaging data. The method and apparatus for processing neuroimaging data provided by the present invention improve the accuracy of neuroimaging data processing.

The invention discloses a brain tumor space-occupying brain network neural image fusion method based on deep learning, and relates to the technical field of artificial intelligence and medical image analysis. The method comprises the following collaborative operation steps: multi-modal brain network data fusion acquisition, tumor occupation effect modeling, functional connection feature dynamic enhancement, cross-modal feature competitive fusion, deformation brain network topology optimization, resistance feature consistency constraint, dynamic loss adaptive regulation and clinical interaction verification. According to the invention, a hybrid architecture based on a graph neural network (GNN) and a three-dimensional convolutional neural network (3D-CNN) is constructed, and structural deformation of tumor occupation and functional network recombination are respectively modeled through a space-function double-flow feature extraction module; in order to solve the problems of brain network dynamic adaptation and multi-modal feature redundancy in the prior art, a channel-graph attention collaboration mechanism is provided, key brain region features are dynamically screened by using a functional connection matrix, and dissection rationality of tumor infiltration boundaries is tracked and constrained in combination with white matter fiber bundles. And finally, a multi-dimensional image map fusing the tumor occupation effect and functional network reconstruction is output, and a quantitative basis is provided for preoperative planning and prognosis evaluation.

The present invention discloses a magnetic susceptibility tensor imaging method and system that separates microstructure-related frequency shifts, including: using a three-dimensional flow-compensated gradient echo sequence to scan and collect 16-channel multi-echo complex data S in six head directions, and preprocessing the 16-channel multi-echo complex data S collected in each head direction to obtain multi-echo phase data in six head directions and multi-echo amplitude data in six directions; the six head directions are specifically head anteroposterior, head posterior, head left, head right, head prone, and head supine; based on the multi-echo amplitude data in the head anteroposterior direction, a template M of the brain region of interest is obtained, and the multi-echo amplitude data in other directions are aligned with the echo amplitude data in the head anteroposterior direction to obtain a registration matrix. The method and system of the present application can better describe the magnetic susceptibility distribution of white matter regions and improve the accuracy of quantitative measurement of magnetic susceptibility.