60 results about "Brain lesions" patented technology

The invention discloses a brain lesion nuclear magnetic image Transform diffusion segmentation method and a brain lesion nuclear magnetic image Transform diffusion segmentation system based on symmetry prior. The invention provides a novel prior-guided diffusion denoising brain lesion segmentation Transform model, long-distance coding features are extracted from an image, local information related to medical image prior features is supplemented, and frequency domain screening fusion coding components are further introduced. A U-shaped denoising model is designed based on a transform network structure, and in order to maintain accurate lesion-related semantic details, a prior feature coding branch is introduced. A priori feature coding branch considers modal-related voxel distribution characteristics and spatial symmetry in a modal, so that a priori guidance attention mask is learned, and attention weights of a pixel level and a patch level are dynamically adjusted. In order to eliminate image noise and a low contrast effect, in a decoding part, a three-branch wavelet frequency spectrum mixed attention module is designed for fusing and screening frequency spectrum feature embedding, and a stable segmentation result is further generated.

The invention provides a deep brain stimulation method and system based on controllable current vectors of high-channel-number electrodes, and the method comprises the following steps: implanting two electrodes into a target region, and enabling a nucleus of the target region to be located between the two electrodes; by selecting different contacts on the stimulating electrodes, multiple channels of induced currents in different directions are generated in a plane constructed by the two electrodes; vector current is formed through vector superposition of the induction current of each channel, and the vector current acts on the target nuclei. The high-channel-number electrodes are adopted, programming control is carried out between the two electrodes, accurate control over current vectors is achieved, control over the magnitude and direction of target region nuclei stimulation current is accurately achieved through current vector superposition, therefore, a brain lesion area can be stimulated more accurately, meanwhile, the current vectors can be accurately controlled, and the stimulation effect of the brain lesion area is improved. And unnecessary current is prevented from diffusing to surrounding normal brain tissues, so that side effects caused by stimulation of a non-target area are reduced.

Among the various aspects of the present disclosure is the provision of a noninvasive and localized brain liquid biopsy using focused ultrasound. Briefly, therefore, the present disclosure is directed to methods and systems to identify brain lesion or tumor characteristics without the need for a solid brain biopsy.

The invention discloses a brain lesion detection method and system based on multi-modal data, and relates to the technical field of brain disease detection. The invention discloses a brain lesion detection system based on multi-modal data. The brain lesion detection system comprises a brain lesion detection triggering module, a brain lesion detection primary screening module and a brain lesion detection secondary screening module. According to the method, screening is performed in combination with current and historical treatment records, so that potential brain lesion clues can be found earlier, and the possibility of early diagnosis is improved; a brain variation feature extraction model is combined with a disease-medication-parameter element path and three attention channel feature extraction method, so that lesion features can be analyzed more comprehensively and deeply, and the accuracy of preliminary screening is improved; a multi-stage elimination mechanism is introduced through a brain transformer accurate re-screening model, and parallel mixed feature analysis and time-space data are combined, so that misjudgment can be effectively reduced, and the accuracy of final diagnosis is improved.

The invention relates to the technical field of disease analysis, and provides an acute-stage cerebral infarction detection system and method.The method comprises the steps that basic information, physical sign data and blood sample data of a brain patient are collected, and data integration is conducted to obtain integrated data; a brain scanning image is obtained, and a high-definition brain image is obtained after artifacts are removed; recognizing image semantics, performing image segmentation, evaluating a segmentation level, and obtaining a target image when a preset level is met; identifying brain lesion features by using the target image; an angiogram is collected, the brain blood vessel caliber is calculated, and the brain blood perfusion condition is analyzed; constructing a blood vessel network by using the angiogram, and analyzing a blood vessel variation degree; based on the blood vessel caliber, the blood perfusion condition and the blood vessel variation degree, analyzing the brain blood vessel lesion degree; collecting an electroencephalogram, and analyzing brain activity characteristics; and performing acute-stage cerebral infarction analysis based on the integrated data, the brain lesion features, the brain vascular lesion degree and the brain activity features. The invention aims to improve the rationality of acute cerebral infarction detection.

The invention discloses a grip strength detection device for brain lesion detection of old people. The grip strength detection device comprises a grip strength extrusion supporting device, a bilateral feedback pushing component and a wrapping feedback component. The invention belongs to the field of medical instruments, and particularly relates to a grip strength detection device for brain lesion detection of old people. By means of the grip strength extrusion supporting device, feedback of detection results of time and grip strength can be visually obtained in the feedback regulation and control panel, meanwhile, the feedback pushing components on the two sides can be operated according to the actual use condition, resistance grip strength detection is achieved by driving the extrusion components to push the bidirectional pushing components, and the detection accuracy is improved. In the detection process, the interestingness of detection is increased, the detection result of the grip strength is fed back more truly, the whole process is short in time consumption and fast in rhythm, efficient and accurate measurement is achieved, the problem that detection is not convenient enough in the early stage of brain lesions of old people is solved, the exposure time of the lesions is shortened, and suggestions and guidance are provided for the next diagnosis and treatment direction.

The invention discloses an application of IPA in chronic pressure-induced brain lesion, relates to the technical field of medicines, and particularly relates to an application of IPA in screening of drugs for treating or preventing chronic pressure-induced brain lesion, and the drugs for treating or preventing chronic pressure-induced brain lesion refer to the application of IPA in screening of drugs for treating or preventing chronic pressure-induced brain lesion. The medicine can reduce the IPA level in a brain region and plasma, and reduce the number of microglial cells in the brain and the expression of an inflammatory factor IL-1beta. The research finds that the IPA level is abnormally increased in the hippocampal brain region and plasma of a mouse model with the chronic pressure-induced brain region lesion, and the improvement of the IPA level in the brain region of a normal mouse can obviously cause the chronic pressure-similar depression behavior of the normal mouse, so that the medicine for treating or preventing the chronic pressure-induced brain region lesion can be screened out; and a theoretical basis and a clinical basis are provided for research on prevention and treatment of chronic pressure similar depression behaviors.

The application discloses an auxiliary identification method for brain inflammatory pseudotumor MRI images based on machine learning, and belongs to the technical field of medical image processing, and comprises the following steps: acquiring preoperative magnetic resonance imaging (MRI) data of a brain lesion of a to-be-measured individual, and performing standardization preprocessing on the MRI data to obtain a standardized brain MRI image; a lesion target region containing a tumor core region and a peritumoral edema region is segmented on the standardized brain MRI image, and a training set, a verification set and a test set are generated based on the lesion target region; a lesion type auxiliary identification model is constructed based on feature screening and feature topology graph attention network of SVM weights, and the training set and the verification set are used for training; the test set is input into the trained lesion type auxiliary identification model to obtain a lesion type identification result, and the problems of time-consuming and labor-consuming, low efficiency, omission of hidden dangers, low accuracy and the like in existing artificial visual measurement and traditional image processing measurement methods are solved.

A system and method automatically detect, in MR images, WM lesions exhibiting a central vein sign. A set of MR images of a brain lesion is acquired, using images of the set as input to different ML algorithms. A first ML algorithm classifies inputted image(s) into first or second classes. The first class includes CVS+ / − and the second class CVSe lesions. A second ML algorithm classifies inputted image(s) into third or fourth classes. The third class includes CVS+ lesions and the fourth central vein sign− lesions. For each set, probability values are used that the set belongs to classes as inputs to a final classifier performing a final classification of the set into second, third, or fourth classes. For each class, the final classifier outputs final probability that the set belongs to the class. The second, third or fourth class with highest probability value is provided through an interface.

This invention relates to the field of biomedicine, disclosing a drug carrier, its construction method, and its applications. The nanoprobe of this invention uses fluorescent nanomaterials as a matrix, with polysaccharide ligands and photosensitizers coupled to it. The polysaccharide ligands cross sugar-specific transport channels on the bacterial cell membrane to enter the bacterial interior, simultaneously carrying the photosensitizer into the bacteria. The inactivated bacteria lose their microbial activity but retain their ability to cross the blood-brain barrier, reaching brain lesions to deliver drugs. Furthermore, the photosensitizer can be used for photothermal therapy of central nervous system diseases such as brain tumors and inflammatory infections under light conditions.

The application discloses a brain deep lesion space position positioning device and method in the technical field of neurosurgical instruments, and relates to the technical field of medical devices. The device comprises an ultrasonic probe, a sliding rail fixedly connected with the ultrasonic probe, and a coaxial biopsy needle in sliding connection with the sliding rail. The coaxial biopsy needle comprises a fixed sleeve fixedly connected with the sliding rail, a needle sheath penetrating through the fixed sleeve, a needle sheath limiter connected with the needle sheath, a needle core penetrating through the needle sheath, and a needle core limiter fixedly connected with the needle core. The needle core limiter is in sliding connection with the sliding rail. The application can solve the technical problem that, when facing brain deep lesions, the existing technology has the problems of brain drift in traditional navigation and insufficient path visibility caused by simple ultrasonic guidance, and cannot accurately guide the puncture path.

Some methods of analyzing one or more brain lesions of a patient comprise, for each of the lesion(s), calculating one or more lesion characteristics from a first 3-dimensional (3D) representation of the lesion obtained from data taken at a first time and a second 3D representation of the lesion obtained from data taken at a second time that is after the first time. The characteristic(s) can include a change, form the first time to the second time, in the lesion's volume and / or surface area, the lesion's displacement from the first time to the second time, and / or the lesion's theoretical radius ratio at each of the first and second times. Some methods comprise characterizing whether the patient has multiple sclerosis and / or the progression of multiple sclerosis in the patient based at least in part on the calculation of the lesion characteristic(s) of each of the lesion(s).

A biomarker predictive of a survival outcome of a brain tumor patient is disclosed. The biomarker includes a functional connectivity matrix that includes a plurality of matrix elements. Each matrix element includes a correlation of resting-state fMRI activities of a first and second region of interest from a plurality of regions of interest within the patient's brain. Computing device and systems are disclosed to transform a resting-state fMRI dataset obtained from the patient into the biomarker and to transform the biomarker into a predicted survival outcome using a machine learning model.

Among the various aspects of the present disclosure is the provision of a noninvasive and localized brain liquid biopsy using focused ultrasound. Briefly, therefore, the present disclosure is directed to methods and systems to identify brain lesion or tumor characteristics without the need for a solid brain biopsy.

The invention relates to a complete set of 3D (three-dimensional)-assisted light-guided puncture orienting equipment and an orienting method thereof, and belongs to the field of medical instruments. The complete set of 3D-assisted light-guided puncture orienting equipment comprises two infrared or laser linear positioning lamps which are arranged on the scalp of a patient and face the head of the patient, and the two linear positioning lamps are arranged on one or two supports through angle adjusting devices; light of the two linear positioning lamps can be adjusted at any angle on the periphery of the scalp, the linear light of the two linear positioning lamps is in different directions, linear light rays formed by the two linear positioning lamps respectively pass through two positioning marks on the periphery of the scalp of a patient, and the puncture catheter is arranged on an extension line of a puncture center line outside the head. The brain focus puncture orienting device can cope with puncture orienting of various brain focuses, damage caused by contact of surgical instruments with the face and the five sense organs of a patient is avoided, and accurate and rapid orienting can be achieved.

Some methods comprise, for each of one or more lesions of a patients brain, from data taken at first and second times, determining two or more lesion characteristics including a lesion's volume change and whether the lesion moved toward a center of the brain. Some methods comprise, for each lesion, determining whether one or more criteria are satisfied, including a volume-and-displacement-based criterion that is satisfied when the change in the volume of the lesion is less than zero and the lesion moved toward the brain's center or the change in the volume of the lesion is greater than zero and the lesion did not move toward the brain's center. Some methods comprise characterizing whether the patient has multiple sclerosis and / or the progression, regression, or stability of multiple sclerosis based at least in part on the assessment of the one or more criteria for each of the lesion(s).

The invention relates to the compound (2S,3S,4R,5R,6S,8R,9S,11R,15R)-3,5,15- triacetoxy-6(17)-epoxy-8-hydroxylathyrane-12E-en-14-one, also called (8R)-8-hydroxyepoxyboetirane A, as well as to a method for obtaining same and the use thereof to promote neuronal differentiation from neural precursors or neural stem cells in culture and in brain lesions. The invention also relates to the use of this compound to prepare a pharmaceutical composition that can be used to treat central nervous system lesions associated with neuron loss.

The invention provides a rare brain lesion distinguishing method based on meta-learning, belongs to the technical field of medical information intelligent diagnosis, and solves the problems that traditional artificial intelligence training needs a large amount of clinical diagnosis information, and the traditional artificial intelligence training needs a large amount of clinical diagnosis information from the data level. And the number of samples of some disease patients cannot meet the requirements of traditional neural network training. According to the technical scheme, a data set of a brain nuclear magnetic resonance image is divided into a plurality of tasks, and each task comprises a support set and a query set; training and testing the CNN model on a pre-training task, and obtaining a globally optimal initialization parameter theta through back propagation; fine-tuning the trained model by using a support set in the new category data set; and testing by adopting the query set to obtain evaluation on the model. The method has the beneficial effects that the prior experience of distinguishing common brain diseases is utilized to generate diagnosis opinions for rare diseases, and the generalization ability of the model is remarkably improved.

Glioblastomas (GBMs) are primary brain lesions with poor overall survival rates. Nearly 95% of patients die within 5 years of primary diagnosis. One of the leading factors to this high mortality is the inevitable nature of cancer recurrence. Disclosed herein are methods and compositions related to the identification and treatment of glioblastoma. Specifically, disclosed herein are methods for identifying progressing glioblastoma, and distinguishing it from pseudo-progression.

The present application belongs to the technical field of ultrasonic physiotherapy, and discloses a transcranial ultrasound treatment fixing method and a helmet based on individual skull image 3D printing. The main process is as follows: MR and CT imaging technology is used to scan the head of a patient to collect data, the system marks the brain lesion of the patient according to the collection result, and then obtains a tomographic optimized data set for training an artificial intelligence model, and finally realizes automatic generation of a solid helmet model with the help of artificial intelligence. The helmet is made by a 3D printer according to the generated model, and at the same time, the installation hole of the ultrasound treatment head is generated in the process of making the helmet, which is used to install the ultrasonic transducer, so as to ensure that the power size, frequency amplitude, incident angle of the ultrasonic wave and the distance between the ultrasonic transducer and the affected area reach the best state, forming customized treatment for different patients. In addition, the helmet model is also provided with a nose frame, which is placed on the patient's nose bridge when worn, which can prevent the helmet from displacement and inclination, thereby ensuring the accuracy and reliability of the helmet installation of the ultrasonic head.

The present invention discloses a monitoring electrode setting method for parietal and temporal lobe lesions. The method utilizes the characteristic that the change of internal impedance of an object will be presented in the change of electrode potential, and optimizes the corresponding monitoring electrodes for the lesions occurring in the parietal and temporal lobes; adopts a relative excitation mode, collects boundary voltage, and performs basic imaging; determines the current lesion position according to basic imaging, and then sets the main electrode and the auxiliary electrode according to the different areas where the lesions are located, and closely arranges the remaining electrodes on both sides of the main electrode to maximize the relative sensitivity of the target area; then selects the electrode pair in turn, moves the electrode pair to the auxiliary electrode, and screens the optimal electrode pair position according to the imaging quality based on RS, BR, and PE, and fixes the electrode pair to the optimal electrode pair position. The present invention optimizes the imaging results of high-probability locations of brain lesions and provides high-quality visualization distribution of internal conductivity of the head.

The invention discloses a head limiting device for craniocerebral focus detection, and relates to the technical field of medical treatment. The device comprises a protection plate, and the top of the protection plate is fixedly connected with a neck support; a fixing device is arranged at the top of the protection plate and comprises a fixing plate, and the side face of the fixing plate is fixedly connected with the side face of the protection plate. According to the invention, a rotating handle is rotated to drive a reciprocating screw rod to rotate force to be matched with a fixed rod, a movable rod, a rotating rod and other components in the fixing device, so that the effect of driving a limiting block to displace through the displacement of a mounting plate is realized, and the effect of fixing and limiting the head of a patient is achieved; it is ensured that the head of a patient keeps stable and fixed in the detection process, it is crucial to ensure that a doctor can obtain clear and accurate focus position information, more accurate diagnosis and treatment planning are facilitated, and the patient can feel more relaxed and comfortable in the detection process.

This invention discloses an extracellular nanovesicle derived from *Acorus tatarinowii* and its applications, belonging to the field of biomedical technology. This invention extracts an extracellular nanovesicle from *Acorus tatarinowii* that possesses both anti-neuroinflammatory and blood-brain barrier penetration capabilities. Loading these nanovesicles with siRNA drugs for treating Alzheimer's disease enables efficient delivery of siRNA to the brain lesions, increasing drug concentration in the brain and achieving a synergistic effect. Compared to synthetic nanocarriers, this is more suitable for long-term administration, providing an advantage for the chronic treatment of Alzheimer's disease. The extracellular nanovesicles of this invention can load siRNAs targeting different pathogenic genes, achieving simultaneous intervention on multiple pathogenic links in Alzheimer's disease, and possessing the potential for multi-target synergistic therapy, which is expected to more effectively halt the progression of Alzheimer's disease.

The application discloses a middle cerebral artery high-density sign identification method, device, equipment and storage medium. In the identification method, first, the middle cerebral artery region of a brain CT plain scan image is extracted to obtain a region extraction image; then, according to a blood vessel enhanced image corresponding to the region extraction image, position information of a middle cerebral artery high-density sign candidate box is obtained; then, texture features are obtained according to the region extraction image and the position information, and shape features are obtained according to the blood vessel enhanced image and the position information; finally, a middle cerebral artery high-density sign identification result is obtained according to the texture features and the shape features. The application can realize accurate and reliable identification of HMCAS in a complex brain lesion environment, and has strong adaptability to scanning equipment and individual imaging differences.

The present application relates to the field of medical image processing and the field of deep learning, and is a kind of brain lesion region positioning system and method for multi-modal image, the system comprises adaptive multi-modal patch growth and pruning module, multi-modal patch multi-level fusion module based on double attention mechanism and global convolution network classifier module, through adaptive multi-modal patch growth and pruning module, patch is adaptively selected and built in multi-modal image, to identify the patch position with high discriminability;Through a kind of multi-modal patch fusion module based on double attention mechanism, the potential representation form of multi-modal patch is obtained, the multi-level representation form of patch is combined, and they are fused and learned together based on data-driven mode;Through global convolution network classifier module as the final classification model, further obtain the deeper representation of data, extract more potential information.The system proposed in the present application can effectively identify the lesion area highly related to the disease, and can assist in diagnosis.

The application provides an electrode assembly and system for accurate positioning of a deep brain lesion target. The electrode assembly comprises a first catheter and an electrode probe. The first catheter comprises a penetration end, an exit end and a catheter body, and the exit end is provided with at least one blocking part. The electrode probe comprises a proximal end and a distal end, and the distal end is arranged in the first catheter and is arranged offset relative to the central axis of the first catheter; wherein the electrode probe can rotate around the central axis in the first catheter to adjust the offset position of the distal end in the first catheter, so that the distal end can avoid the blocking part or be blocked by the blocking part to bend relative to the central axis of the first catheter during the process of penetrating out of the first catheter. By adjusting the rotation of the electrode probe in the first catheter, the distal end can select different penetration paths, and a large range of electrophysiological signal collection is realized, which is helpful for accurately positioning the position relationship between the stimulating electrode and the target nucleus.

The present application relates to a kind of agglutinin joint targeting peptide modified nanosphere and its preparation method and application, belong to the biomedicine technical field.To solve the problem that the existing drug delivery system is difficult to have the integration of nasal brain barrier breakthrough, nasal long-term retention, brain lesion targeting, broad-spectrum drug loading and high biological stability, the present application provides a kind of agglutinin joint targeting peptide modified nanosphere, including polymer matrix core, biomimetic cell membrane shell and double-ligand functionalization surface crown layer in turn from inside to outside.The nanosphere of the present application can prolong the nasal retention time and efficiently penetrate the nasal mucosa barrier by relying on the synergistic effect of core-shell-crown three-layer structure, realize transnasal brain and lesion precise targeting, improve drug delivery efficiency and efficacy, and reduce toxic side effects.The nanosphere of the present application has a wide range of drug loading spectrum, suitable for the drug demand of various central nervous system diseases, and has excellent clinical transformation value and application prospect.

The invention discloses an engineered brain-targeted delivery cell as well as a preparation method and application thereof. The engineered brain-targeted delivery cell is prepared by carrying out modification treatment on the surface of the cell by using a modifier, wherein the modifier comprises a cationic material, alkaloid and / or polysaccharide. The method provided by the invention aims to overcome the problem that the cells are difficult to efficiently pass through the blood brain barrier (BBB) or effectively target the brain lesion site in the existing cell therapy. Through the above surface modification strategy, the tropism and retention ability of the modified cells to the brain microenvironment are significantly enhanced, so that the enrichment efficiency of the cells in the brain is improved. The modified cells obtained on the basis of the method are suitable for preparing drugs or cell preparations for treating various brain diseases. The brain diseases include but are not limited to cerebral apoplexy, Alzheimer's disease (AD), Parkinson's disease, brain tumor and the like. The method provides an important technical means for developing a novel and efficient brain disease cell treatment strategy, and has potential clinical application value.

The invention relates to a bionic nano delivery platform for brain targeting and photothermal therapy, a preparation method of the bionic nano delivery platform and application of the bionic nano delivery platform in treatment of neurodegenerative diseases. The platform is composed of a drug-loading core and a functionalized shell, wherein the drug-loading core is a cycloastragenol-loaded liposome; the functionalized shell covers the drug loading core and is composed of a microcolloid cell membrane and a near-infrared two-region photo-thermal material dispersed in the microcolloid cell membrane. According to the structure, through cell membrane bionic modification, a platform is endowed with good brain focus targeting, efficient immune escape ability and a remarkable drug enrichment effect, and collaborative delivery and controlled release of cycloastragenol and a photo-thermal material can be achieved. The platform and the system have the comprehensive advantages of being accurate in brain targeting, remarkable in treatment synergistic effect and good in biocompatibility, and have wide clinical application prospects in the field of targeted therapy of neurodegenerative diseases.

The application discloses a brain lesion detection method and system based on multi-modal data, and relates to the technical field of brain disease detection. The brain lesion detection system based on multi-modal data comprises a brain lesion detection triggering module, a brain lesion detection preliminary screening module and a brain lesion detection re-screening module. The application can discover potential brain lesion clues earlier and improve the possibility of early diagnosis by screening current and historical medical records. The brain lesion feature extraction model, the disease-drug-parameter meta path and the three-attention channel feature extraction method can comprehensively and deeply analyze lesion characteristics and improve the accuracy of preliminary screening. The multi-level elimination mechanism is introduced by the brain lesion accurate re-screening model, and the parallel mixed feature analysis and space-time data are combined, so that the false judgment can be effectively reduced and the accuracy of the final diagnosis can be improved.