764 results about "Brain tissue" patented technology

The invention provides an acute cerebral apoplexy early-stage intelligent screening and early warning method and system based on deep learning, and relates to the technical field of medical imaging and artificial intelligence, and the method comprises the steps: obtaining a multi-temporal angiography image of the brain of a patient through a pulse-type dynamic imaging scheme, extracting hemodynamic features through a double-flow feature extraction network, and obtaining a multi-temporal angiography image of the brain of the patient; and constructing a vasculopathy risk distribution diagram by combining a vascular structure analysis model, and marking a potential embolism risk area. Furthermore, in combination with tissue perfusion parameters obtained by multispectral imaging and brain tissue function parameters obtained by electroencephalogram signals, an ischemic penumbra region is identified by using a self-adaptive threshold segmentation model. And finally, based on the ischemic penumbra area, the tissue perfusion parameters and the brain tissue function parameters, calculating a risk level by using a hierarchical decision model with a space-time attention mechanism, and generating a corresponding clinical intervention scheme. According to the invention, the early accurate screening and risk early warning of acute cerebral apoplexy can be realized, and the clinical intervention efficiency is improved.

A histotripsy therapy system configured for the treatment of brain tissue is provided, which may include any number of features. In one embodiment, the system includes an ultrasound therapy transducer, a drainage catheter, and a plurality of piezoelectric sensors disposed in the drainage catheter. The ultrasound therapy is configured to transmit ultrasound pulses into the brain to generate cavitation that liquefies a target tissue in the brain. The drainage catheter is configured to detect the ultrasound pulses. An aberration correction algorithm can be executed by the system based on the ultrasound pulses measured by the drainage catheter to automatically correct for an aberration effect caused by the ultrasound pulses passing through a skullcap of the patient.

The invention relates to the technical field of medical monitoring and early warning, and discloses a postoperative care risk early warning system for neurosurgical patients. According to the system, real-time monitoring flows of electroencephalogram, intracranial pressure and body surface myoelectricity of a patient are continuously received, and a dynamic interaction network of neuroelectrophysiology and intracranial mechanical states is constructed so as to represent the coupling relation among electroencephalogram rhythm, pressure conduction and postoperative skull windowing area tissue compliance. The system analyzes three types of core parameters of cerebral cortex excitability, cerebrospinal fluid circulation load and cranial cavity compensation space from the network, further calculates a brain tissue perfusion risk and a neural structure compression risk, and generates a corresponding nursing early warning signal and a physiological regulation path. According to the scheme, deep coupling and mechanism risk early warning of multiple physiological signals are achieved, and the postoperative complication risk can be recognized earlier and more accurately.

Systems and methods for predicting and managing seizures in an individual are disclosed. In one aspect, a method for predicting and managing seizures in an individual. In another aspect, a system comprising an implanted device configured to capture at least one measurement of an impedance of brain tissue of an individual and a computing device configured to. in response to a prediction that the individual is likely to experience a seizure, initiate a remedial action that comprises at least one of alerting the individual or another user that the individual is likely to experience the seizure, applying an electrical stimulus to the brain tissue of the individual to reduce a likelihood of the seizure occurring or to reduce a severity of the seizure, or delivering a drug to the brain tissue of the individual to reduce a likelihood of the seizure occurring or to reduce a severity of the seizure.

The invention relates to a transcranial magnetic stimulation high-precision positioning method, device and equipment based on optical navigation. Comprising the steps of selecting non-coplanar reference points based on a three-dimensional brain model of a patient, obtaining image coordinates and physical coordinates of all the reference points, carrying out corresponding point matching through the image coordinates and the physical coordinates, calculating and generating an optimal rigid transformation matrix, carrying out target registration error calculation, and realizing registration of an image coordinate system and a physical coordinate system. And according to the registered brain tissue conductivity parameters, calculating electric field space distribution induced by the transcranial magnetic stimulation coil in a target brain area, dynamically correcting stimulation target point coordinates of the virtual coil, and according to a completed coordinate system registration result, dynamically displaying the position and direction of the virtual coil corresponding to the transcranial magnetic stimulation coil on the three-dimensional brain model. And synchronously updating the brain slice view based on the corrected target point coordinates, and highlighting the actually stimulated brain region boundary. According to the method, adaptive neural navigation is driven through electric field remapping, and compensation target point correction is achieved.

The invention relates to the field of biomedicine, and particularly discloses an epileptic focus artificial intelligence positioning system and method based on magnetic resonance and electroencephalography, and the system comprises the following contents: a data collection module is used for synchronously collecting T1 weighted magnetic resonance images and electroencephalogram signals of scalp; the data preprocessing module is used for performing brain tissue segmentation on the magnetic resonance image, obtaining structural features of each brain region, constructing vectors including whole brain structural features, and obtaining magnetic resonance structural feature vectors; artifacts of the electroencephalogram signals are removed, electroencephalogram features of all brain areas are extracted through time-frequency analysis, a matrix containing whole electroencephalogram physiological features is constructed, and the electrophysiological features are obtained; the cross-modal confidence coefficient dynamic evaluation module is used for establishing a bidirectional constraint rule to perform confidence coefficient calibration on the magnetic resonance structure feature vector and the electrophysiological feature; a positioning model construction and training module; a positioning result output module; according to the technical scheme, noise can be reduced during magnetic resonance and electroencephalogram fusion, and the epileptic focus positioning precision is high.

The invention discloses a tumor space-occupying brain network neural image alignment method based on multi-modal fusion, and belongs to the technical field of medical image processing and artificial intelligence crossing. The method comprises the following core steps of multi-modal image heterogeneous feature decoupling, tumor occupation deformation field modeling, functional network topological structure maintenance, cross-modal feature adversarial alignment, dynamic deformation constraint optimization and clinical interpretability verification, and construction of a three-dimensional non-rigid registration network based on a double attention mechanism. And differential homeomorphic mapping of a tumor focus area and normal brain tissue is realized through the cascaded spatial transformation module. Aiming at the problems of insufficient multi-modal feature alignment and brain network topology distortion in the prior art, the invention provides a function connection constrained cross-modal fusion strategy, a graph convolution network is adopted to encode resting state function connection features, and network node displacement caused by tumor occupation is dynamically corrected in combination with deformable convolution and a bidirectional feature competition mechanism; a space consistency loss function based on white matter fiber bundle tracing is designed, and through diffusion tensor imaging feature guide structure-function bimodal joint optimization, the problems of insufficient registration precision in a focus area and whole brain network connection distortion of a traditional method are solved. Experiments show that the registration precision of the method in glioma cases reaches 0.82 mm and is improved by 37% compared with that of a traditional method, and dissection-function consistency of functional network reconstruction around tumors is remarkably improved.

The invention belongs to the technical field of biological medicines, and particularly relates to application of a targeted liposome as an active component in preparation of a medicine for treating ischemic brain injury. The targeted lipidosome for treating cerebral arterial thrombosis is prepared by fusing the lipidosome and the platelet-neutrophil aggregate membrane, realizes efficient and specific targeting of an ischemic brain region, effectively reduces brain tissue infarction and damage of a new region, relieves brain inflammation through multi-channel regulation and control, and improves the cerebral arterial thrombosis treatment effect. The compound can be used as an active ingredient for preparing a medicine for treating ischemic brain injury. And after the target liposome is further coated with a rutin drug, the synergistic treatment effect is realized. The liposome medicine can be used as an active component and has a good application prospect in treatment of ischemic brain injury diseases.

A neurosurgery system for probing brain tissue of a patient for tumorous tissue. The system including a suction tool, an excitation source, an optical instrument, and a controller. The suction tool including a suction cannula defining a lumen, an optical fiber configured to transmit fluorescence emitted by the brain tissue; and an indicator configured to selectively emit visible light. An excitation source is configured to emit an excitation light having a wavelength to induce the fluorescence in the tumorous tissue. The optical instrument is coupled to the optical fiber. The optical instrument configured to convert the fluorescence emitted by the brain tissue and transmitted by the optical and configured to determine that the brain tissue is tumorous based on the electrical signal and activate the indicator based on the determination.

A computer system that performs quality control (QC) on images associated with diffusion and structural magnetic resonance imaging (MRI) is described. This computer may include: a computation device that executes program instructions; and memory that stores the program instructions. During operation, the computer system may automatically perform a set of validation operations, where, when one or more of the validation operations fails, the images are rejected. Moreover, the set of validation operations may include: performing QC on brain-tissue segmentation; performing QC on diffusion MRI processing; and performing QC on bundles determined from the images using a tractometry technique.

The present disclosure provides anti-transferrin receptor antibodies, compositions comprising the same and methods of use for delivery of cargo to brain tissue. This disclosure also provides polynucleotides and vectors encoding the anti-transferrin receptor antibodies and cells comprising the same, methods of making the antibodies, and molecules comprising the antibodies.

An ultrasound transducer assembly is connectable to an ultrasound system and comprises one or more ultrasound transducer elements supported by a cap. The ultrasound transducer elements are operable to direct ultrasound energy toward brain tissue of a subject and / or to receive echo ultrasound energy when the ultrasound transducer assembly is mounted on the head of the subject. Some embodiments include a fillable jacket coupled to the inner surface of the cap and in acoustic contact with the one or more transducer elements.

The invention belongs to the technical field of nerve regulation and control engineering, and provides a cerebrospinal fluid rhythm-based Alzheimer's disease electrical stimulation system, which is characterized in that first frequency band range data and second frequency band range data in brain wave signals are coupled to obtain cerebrospinal fluid rhythm data; then, calculating the phase difference between the first frequency band range data and the cerebrospinal fluid rhythm data; finally, the stimulation frequency is dynamically controlled according to the phase difference, and the stimulation current is dynamically controlled according to the brain tissue water volume fraction. The problem that specific metabolism requirements of non-fast eye movement sleep and fast eye movement sleep cycles cannot be matched by adopting single-frequency-band stimulation is solved, dynamic changes of post-traumatic encephaledema and requirements and influences of cerebrospinal fluid rhythm on current control are considered, the real-time adaptive capacity to the dynamic changes of the post-traumatic encephaledema is improved, and the application prospect is wide. And the treatment effect of the Alzheimer's disease is ensured.

The invention discloses a stimulating electric field display method, device, system and equipment, a medium and a product. The method comprises the steps that in response to a model display operation, a target object and a brain tissue image model corresponding to the target object are determined, and the brain tissue image model comprises at least one deep brain stimulation electrode model; in response to the electrode configuration operation, determining electrode configuration information and stimulation parameter application information of each electrode model; and in response to an electric field display operation, determining program-controlled electric field information of at least one electrode model under the electrode configuration information and the stimulation parameter application information, and displaying the program-controlled electric field information on the displayed brain tissue image model. Based on the technical scheme of the invention, the effect of quickly calculating and displaying the distribution condition of the program-controlled electric field simulated by any electrode configuration and the electrode model under the applied voltage on the brain tissue image model can be realized, and a technician can be effectively assisted in performing deep brain stimulation electrode configuration.

The invention provides an implantable nerve probe integrated with a biological protection layer, a preparation method and a system. The nerve probe sequentially comprises a bottom biological protection layer, a bottom flexible substrate layer, a conductive layer, a top flexible substrate layer and a top biological protection layer from bottom to top, the bottom biological protection layer and the top biological protection layer form a biological protection layer located on the outermost periphery of the nerve probe and are used for avoiding erosion of a damp and hot cerebrospinal fluid environment in brain tissue. The integrated biological protection layer located on the outermost periphery of the flexible nerve probe is adopted, corrosion of cerebrospinal fluid to the nerve probe can be inhibited in in-vivo application, the long-term biocompatibility of the flexible nerve probe is effectively improved, the in-vivo long-term service life of the flexible nerve probe is effectively prolonged, and the nerve probe has the advantages of being high in integration level, high in stability and the like; and the requirement of in-vivo long-term effective service of the device can be met.

The invention relates to the technical field of stereotactic surgery, and discloses a neurosurgery stereotactic surgery positioning system based on multi-modal image fusion, which comprises a multi-modal image acquisition module, an intelligent registration fusion module, a three-dimensional modeling module, a surgery navigation engine, an augmented reality interface and a dynamic calibration module, a cross-modal elastic registration module is arranged, when multi-modal image fusion is carried out, the spatial matching degree of a functional image and a structural image is detected in real time through a nonlinear deformation compensation algorithm, and when registration deviation exists between white matter fiber bundles and tumor boundaries, an elastic deformation compensation field is dynamically generated by a system, so that the positioning accuracy of a neural functional area is improved; and by arranging the dynamic drift correction module, the brain tissue displacement change is perceived in real time based on laser surface scanning during deep target navigation, precise correction of the pose of the surgical instrument is realized, and the positioning reliability of the deep target is ensured.

The invention provides a novel geometric shape quantitative analysis method for brain subregion tissues, which is characterized in that depth feature extraction of a CNN-Transform mixed architecture and quantitative characterization of multi-scale differential geometric features are fused, and comprises the following steps: firstly, constructing an SFUNet dual-path encoder, accurately capturing local details of a brain subregion through depth separable convolution, and extracting the local details of the brain subregion; modeling global semantic association of a cross-brain subregion in combination with a Transform branch, dynamically fusing dual-path features, and accurately segmenting an effective brain subregion tissue range; secondly, designing a quantization method from segmentation to spherical harmonic coefficient (SPHARM) mapping according to the geometric morphology of the curved surface of the brain subregion, namely, extracting Gaussian curvature and average curvature point by point after point-to-point registration through standard spherical parameterization and group average curved surface registration, and respectively representing local convex-concave characteristics and bending strength of a specific brain tissue region; and finally, constructing a multi-scale differential geometric feature vector in combination with an SPHARM low-frequency coefficient, and inputting the multi-scale differential geometric feature vector into an AI algorithm to realize brain tissue collaborative analysis of an anatomical structure and geometric deformation.

A portable device for detecting a large vessel occlusion in a patient's brain by transmitting a signal into both sides of the brain and receiving the reflections of the transmitted signals to capture a single reflection data point of the characteristics of the blood vessels and brain tissue on both sides of the brain. Using the captured single reflection data point values to perform a comparative analysis between the right and left side of the brain, and based on this analysis, assessing whether the patient is experiencing a large vessel occlusion. If so, the device generates an alert.

The invention discloses a preparation method and application of yak blood peptide with anti-hypoxia and anti-fatigue functions. The method comprises the steps of raw material pretreatment, composite enzymolysis (adopting a mixture of enzyme digestion modified lumbrukinase and nattokinase), enzyme deactivation, separation and purification, ferrous chelation, Maillard reaction, concentration and drying and the like. The enzymolysis efficiency and the active peptide yield are remarkably improved through ultrasonic treatment and a composite enzymolysis technology, the stability and the anti-hypoxia capacity of peptide fragments are enhanced through ferrous chelation, and the antioxidant activity and the anti-fatigue activity are further improved through the Maillard reaction. Experiments show that the yak blood peptide prepared by the method can significantly improve the antioxidant enzyme activity, prolong the normal-pressure hypoxia survival time, prolong the swimming exhaustion time and significantly reduce the MDA content of brain tissue and myocardial tissue. The obtained product can be applied to anti-hypoxia and anti-fatigue medicines or health-care foods, and has the advantages of high process efficiency, remarkable activity, high safety and the like.

The invention provides application of enhanced and optimized mesenchymal stem cells and exosomes in anti-aging or senescence delaying, and belongs to the technical field of biological medicine manufacturing. According to the pharmaceutical composition disclosed by the invention, the activity-enhanced mesenchymal stem cells and the exosomes secreted by the activity-enhanced mesenchymal stem cells are applied in a combined manner, so that a remarkable synergistic interaction effect is shown in anti-aging intervention. Experiments prove that the composition can systematically improve oxidative stress injury related to aging, significantly recover antioxidant enzyme activity of serum and brain tissue to be close to a normal level, and effectively reverse cognitive function degeneration, which is represented as behavioral improvement such as shortening of escape latency, improvement of spatial memory ability and the like; the invention is suitable for preparing drugs or functional preparations for delaying body aging or resisting aging, and provides an innovative technical path for developing an efficient and safe anti-aging therapy.

The invention is applicable to the technical field of medical instruments, and provides a subskull epidural micro-invasive flexible brain-computer interface electrode, which comprises a plurality of electrode branches, each electrode branch comprises a linear flexible main body, and the flexible main body comprises a micro power supply circuit and a signal circuit which are solidified. A plurality of electrode units are arranged on the micro power supply circuit and the signal circuit at intervals, and the electrode units are electrically connected with the micro power supply circuit and the signal circuit. The brain-computer interface electrode is in a flexible line type, can be implanted into the middle artery of the meninx, does not need craniotomy, is a micro-invasive brain-computer interface, has data monitoring accuracy close to that of an invasive brain-computer interface, does not need to worry about inflammatory response, immunostimulation, biocompatibility, brain tissue damage and other adverse factors after long-term implantation, and is suitable for popularization and application. And the thrombogenic risk of a vein stent brain-computer interface does not exist.

According to the neural regulation target positioning method and system based on magnetic resonance and electroencephalogram fusion and the focus brain tissue head model construction method based on deep learning, the individual brain structure can be accurately simulated, and a reliable basis is provided for subsequent analysis; according to the electroencephalogram source imaging method based on deep learning, a brain source can be effectively positioned from complex electroencephalogram signals; a target network accurate positioning method based on source imaging further locks and regulates a target spot and a target brain network. The combination of the three can give full play to the advantages of multi-modal data, achieves more accurate and efficient target spot and target network positioning by means of the powerful ability of deep learning, and provides powerful support for nerve disease diagnosis and treatment.

The invention relates to the technical field of medical instruments, in particular to a cerebral hemorrhage drainage device with a breaking and sucking function, which comprises a base, a support frame is fixedly mounted at the upper end of the base, a breaking mechanism is arranged on the back of the support frame, and a drainage assembly is arranged in the support frame. Through the arrangement of the crushing mechanism, blood clots and fragments can be effectively crushed and sucked out through the absorption assembly while drainage is conducted, so that it is guaranteed that hematoma is completely removed, the hematoma recurrence risk is reduced, and the drainage effect is improved; by means of the breaking and sucking function, blood clots and fragments are prevented from blocking the drainage tube, it is guaranteed that blood can flow out smoothly, and complications are reduced; by efficiently removing hematoma, compression and injury of brain tissue are reduced, nerve recovery is promoted, and the hospitalization time and rehabilitation cycle of a patient are shortened; blood clots and fragments are effectively removed, the condition of incomplete drainage or blockage is reduced, and the incidence rate of complications such as infection and hematoma recurrence is reduced.

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.

Disclosed are devices, systems, and methods for ultrasonically stimulating brain tissue using operating parameters associated with a. target region of a brain. The operating parameters can be determined, for example, by combined ultrasonic stimulation and photometry devices and methods. The operating parameters can include pulse repetition frequency, temporal compression, and intensity. Using selected operating parameters, ultrasound stimulation of the target region of the brain can excite or inhibit brain cell activity.

The invention provides a self-adaptive cerebral cortex reconstruction system, method and device based on deep learning and a medium, and the reconstruction system comprises an image preprocessing module which is used for preprocessing input MRI image data to obtain a real curvature image, a real brain tissue segmentation image and a real cerebral cortex; the three-stage grid deformation module is connected with the image preprocessing module; the three-stage grid deformation module comprises three continuous grid deformation modules, and each stage of grid deformation module comprises a deformation model and a physical deformation module; the deformation model is used for predicting a curvature perception static velocity field and a curvature graph; and the physical deformation module calculates differential mapping for each vertex position from the curvature sensing static velocity field so as to generate and obtain a final cerebral cortex surface, so that the accuracy and the efficiency of cerebral cortex reconstruction can be remarkably improved.

A method for performing multi-voxel spectroscopy includes obtaining structural magnetic resonance imaging data of a brain of a subject acquired with a magnetic resonance imaging scanner. The method also includes performing skull stripping on the structural magnetic resonance imaging data to generate a skull stripped brain image. The method further includes utilizing a trained deep learning-based segmentation model to generate a lesion core mask from the brain image. The method also includes locating a slice with largest volume of lesion present in the lesion core mask. The method includes calculating a voxel volume that avoids aliasing from the slice based on a field of view. The method includes automatically selecting a volume of interest in the brain having both the lesion and normal brain tissue for a multi-voxel spectroscopy scan by the magnetic resonance imaging scanner based on the brain image, the lesion core mask, and the voxel volume.

A combined neuromodulation and / or neurostimulation system for mitigating locomotor deficits of / or neuronal disorders, especially Parkinson's disease, said system comprises: at least one Deep Brain Stimulation System for providing Deep Brain Stimulation to brain tissue of a subject, at least one control unit, configured and adapted to provide stimulation data, at least one stimulation unit, operatively connected to the at least one control unit, the at least one stimulation unit being configured and adapted to deliver epidural electrical stimulation to the dorsal side of the spinal cord of said subject, and at least one implantable pulse generator, wherein the at least one stimulation unit includes one or more electrodes configured to be implanted epidurally, the one or more electrodes being operatively connected to the at least one IPG.

The utility model provides an integrated stent-type artificial blood vessel which comprises an artificial blood vessel part comprising an artificial blood vessel main branch used for being arranged corresponding to an ascending aorta of a human body; the covered stent comprises a covered stent trunk and a left subclavian artery branch arranged beside the covered stent trunk and communicated with the covered stent trunk; the bendable connecting tube section is arranged between the artificial blood vessel part and the covered stent, the bendable connecting tube section comprises a main tube section and a side short tubular joint which is arranged on the side of the main tube section and communicated with the main tube section, and in the main blood flow direction of the artificial blood vessel, the near end of the main tube section is connected with the main branch of the artificial blood vessel; the far end of the main pipe section is connected with the near end of the artificial blood vessel main branch, and the axial height of the side short pipe-shaped connector is smaller than that of the left subclavian artery branch. The number of branch arteries needing to be dissociated in an operation is reduced, then dissociation anastomosis time is saved, circulation stopping time is shortened, protection on brain tissue is enhanced, and postoperative rehabilitation of a patient is facilitated.

This disclosure describes examples of dual-modality imaging implementations involving both photoacoustic and fast super-resolution ultrasound localization imaging for non-invasive and non-superficial monitoring of both structural information and physiological activities / parameters in tissues. As an example, such dual-modality imaging may be particularly applied to the monitoring of structural information and physiological activities / parameters associated with the blood-brain barrier (BBB) in brain vascular structures that are subject to intervention / modulation (by, e.g., Focused Ultrasound, or FUS) for purposes of drug delivery from a blood flow to brain tissues.