95 results about "Nerve fiber bundle" patented technology

The invention relates to the technical field of medical image recognition, in particular to an ultrasound-guided nerve block liquid medicine diffusion image recognition method, which comprises the following steps of: dynamically analyzing a set with external expansion morphological feature points on a liquid medicine diffusion boundary to construct directional data representing a diffusion trend, and performing density statistics on the directional data to obtain an image recognition result; therefore, the dominant direction of liquid medicine diffusion in space is accurately identified, judgment is carried out in combination with the change trend of the dominant direction in a continuous time frame, a time slice with the stable and continuous direction is screened out, then the method goes deep into a liquid medicine coverage area, the consistency between the pixel gray scale gradient change and the nerve fiber anatomy trend is compared, and the accuracy of the nerve fiber anatomy is improved. Finally, effective classification of the diffusion paths is realized, an effective diffusion area conforming to the trend of the neural structure and a non-dominant diffusion area towards other tissues can be clearly distinguished, and the accuracy and clinical reference value of an identification result are greatly improved.

Methods and apparatus disclosed for treating pain and mobility impairments include synergistic application of various stimuli to a patient. These stimuli can comprise serial and sequential combinations of predetermined subatmospheric pressure values, time-varying voltage waveforms applied to electrodes in contact with different portions of a patient's skin in a matter that produces currents which stimulate nerve fibers that activate muscles, and direct practitioner-assisted mechanical movement of tissue. Apparatus and systems for applying the treatment methods are disclosed.

The embodiment of the invention discloses a brain operation path determination method and device, equipment, a medium and a medical system. The brain operation path determination method comprises the steps that a brain structure model and at least one target spot of a target user are obtained; based on the brain structure model, determining an information transfer relationship between each nuclear group sub-model and each nerve fiber sub-model; determining a plurality of candidate operation schemes based on the plurality of preset path starting points, the target group sub-model to which the at least one target point belongs and the information transfer relationship; for each candidate operation plan, performing quality evaluation on the candidate operation plan based on a quantitative evaluation model under at least one evaluation dimension, and determining a path quality attribute corresponding to each candidate operation plan; according to the method, at least one target recommended operation scheme is determined based on each path quality attribute, a plurality of candidate paths conforming to nerve conduction characteristics are automatically generated, and an optimal scheme is screened through a quantitative evaluation model, so that the brain tissue injury risk and the operation complexity are effectively reduced while the operation precision is improved.

The invention relates to the technical field of neurosurgery navigation, in particular to a neurosurgery brain puncture path accurate planning method and system.The neurosurgery brain puncture path accurate planning method comprises the following steps that by obtaining a preoperative brain function area image and nerve fiber bundle data, a function area range and sensitivity are extracted, a focus and cranial entry point path set is constructed, and a path set is established; the method comprises the steps of analyzing the distance between a path and a functional area and a fiber bundle included angle, calculating a functional interaction risk, dividing path sections and calculating the distances to a blood vessel, a ventricle and the functional area, generating obstacle field intensity and calculating a gradient difference, constructing a risk map, scoring candidate paths, and screening an optimal path to generate a puncture result. The method comprises the following steps: extracting a brain function region range and a fiber bundle direction, introducing a function sensitivity parameter, improving tiny damage identification, calculating obstacle field intensity in a path segmentation manner, forming a gradient, dynamically identifying a high-risk region, grading and screening candidate paths by integrating risk factors, performing function protection and risk reduction, and improving path planning refinement and safety.

The present application relates to the technical field of medical image processing, in particular to an image intelligent analysis system for corneal nerve fibers of dry eye patients, which comprises an image acquisition module, an image preprocessing module, a nerve fiber segmentation module, a nerve morphological analysis module based on differential geometry, a nerve regeneration monitoring module, a data management module and a clinical auxiliary decision module. The nerve morphological analysis module based on differential geometry is the core innovation, which contains a nerve fiber curvature analysis unit, a multi-scale differential invariant extraction unit and a nerve network topology structure quantification unit. The system introduces the theory of differential geometry, represents the nerve fiber through a parameterized curve and calculates the local curvature characteristics. A Gaussian scale space is constructed to extract multi-scale differential invariants. The graph structure representation of the nerve network is established to analyze the topological characteristics. The morphological characteristics of the corneal nerve fibers can be quantified comprehensively from the local curvature to the global topological structure, and the accurate detection of the slight changes of the nerve fibers is realized.

The invention relates to the technical field of biomedical engineering, and discloses a neural conduction pathway quantitative analysis method and system based on a neural potential waveform. The system comprises: a bioelectric signal acquisition module configured to establish a time sequence characterizing the change of neural current over time; the waveform deep learning module is configured to fit conduction waveforms of the A beta nerve fiber, the A delta nerve fiber and the C-type fiber by using a deep learning algorithm based on the time sequence, and identify a peak point of the conduction waveform of each fiber; the quantitative analysis module is configured to calculate the frequency and intensity function of each fiber conduction signal according to the peak point, and the physiological characteristic parameters comprise the myelination degree, the conduction speed and the sensitivity to anesthetics; and the control module is configured to generate a differential blocking strategy aiming at the A beta nerve fiber, the A delta nerve fiber and the C-type fiber based on the frequency and intensity functions and generate the anesthetic dosage. And specific recognition and differential blocking control of A beta, A delta and C type fiber signals are realized.

Differential charge-balancing can be used in high-frequency neural stimulation. For example, a neural stimulation apparatus can have first and second electrodes configured to be coupled proximate to a nerve fiber to implement a neural stimulation procedure. A neural stimulation circuit can be electrically coupled to the first and second electrodes. The neural stimulation circuit can apply stimulation currents to the nerve fiber through the first and second electrodes during a first stimulation phase of the neural stimulation procedure. The neural stimulation circuit can also apply a modified stimulation current to the nerve fiber through the first electrode during a second stimulation phase of the neural stimulation procedure. The modified stimulation current can be generated based on a difference between (i) a voltage at the first electrode, and (ii) a reference voltage derived from voltages on the first and second electrodes.

Systems, devices, and methods for affecting a patient's organ function by innervating one or more organs of the patient are described herein. Innervating one or more organs of the patient is induced via electrical stimulation to nerve fibers, such as afferent nerve fibers, of one or more of the patient's dorsal roots. Electrical stimulation to dorsal root nerve fibers is delivered using at least one intravenous electrode disposed within a vein of the patient proximate to the dorsal root nerve fibers.

The invention discloses a nerve cryoablation puncture needle suite with a nerve stimulation module, and relates to the technical field of medical equipment, the nerve cryoablation puncture needle suite comprises an ultrasonic easy-to-develop puncture needle main body, and the puncture needle main body is connected with a three-way valve; the probe body is connected with the needle body, the delivery pipe is arranged on the surface of the outer end of the needle body, and the other end of the delivery pipe is communicated with the three-way valve and can be used for drug delivery. After the tail end of the needle core is connected with the nerve stimulation module, current can be quantitatively output, the tip of the needle core can stimulate nerve fibers with the diameters from small to large, nerve sensation or movement reaction can be induced, focus-related nervous tissue can be accurately targeted, tissue specificity in the treatment process is ensured, and accuracy and safety of pain treatment are improved. The refrigerating pipe is arranged at the middle end in the needle body, the vacuum cavity is formed in the inner wall of the needle body, when the refrigerating fluid is vaporized and discharged through the outlet, the refrigerating fluid which is not vaporized completely makes contact with the outlet, the filler is cooled and expands to block the outlet, and the refrigerating fluid is effectively prevented from overflowing at low temperature.

The invention provides a method for removing noise signals in a brain-computer interface through a force-electric decoupling method, and the method comprises the steps: collecting signals generated in the brain-computer interface, including electric signals transmitted by nerve fibers, interference electric signals and electric signals caused by force signals of various loads in the brain; electric signals caused by action potential are removed through the force-electricity constitutive relation of the liquid-containing porous material, electric signals caused by force signals of various loads in the brain are decoupled, and electric signals conducted by nerve fibers are reserved. According to the method, noise signals generated due to the electrokinetic effect in the brain-computer interface can be effectively removed, and electric signals conducted by nerve fibers can be accurately obtained.

A method of activating a piezoelectric neuroconduit guide scaffold including a plurality of aligned piezoelectric polymer nanofibers, the method including mechanically stimulating the piezoelectric neuroconduit guide scaffold with hydro-acoustic waves or shockwaves to remotely activate a piezoelectric effect of the nanofibrous scaffolds that induces a mechano-electrical stimulus on neural cells cultured on the scaffold, wherein the mechano-electrical stimulus promotes nerve fiber outgrowth from the neuronal cells. Some aspects relate to seeding individual components of neural tissues on the piezoelectric neuroconduit guide scaffold, wherein the hydro-acoustic stimulation induces neural tissue formation. In other aspects, the piezoelectric neuroconduit guide scaffold is implanted in a damaged neural tissue, wherein stimulating the piezoelectric neuroconduit guide scaffold by the application of shockwaves promotes nerve fiber outgrowth that bridges a nerve gap to induce nerve regeneration or reinnervation of the damaged neural tissue.

The invention discloses a brain tumor potential recurrence risk area determination device and a model training method, and relates to the field of medical science and technology and the field of artificial intelligence. The device comprises a delineation determination unit used for determining a brain tumor delineation area based on a target medical image of a target object; the nerve fiber reconstruction unit is used for simulating and reconstructing image information of N target nerve fibers of the target object according to the target medical image; and the risk area prediction unit is used for inputting the target medical image and the image information of the N target nerve fibers into the target model, performing feature extraction on the received information through the target model, and determining a recurrence risk area of the brain tumor of the target object according to the extracted features by using priori knowledge in a model training stage. According to the method and the device, the technical problem of low accuracy of determining the potential recurrence risk area of the brain tumor caused by judging the risk diffusion condition of the brain tumor only through imaging observation or expert experience in the prior art is solved.

The application discloses a preparation method and application of a nerve conduit with a multistage biomimetic nerve membrane structure and belongs to the technical field of tissue engineering materials. The nerve conduit with the multistage biomimetic nerve membrane structure comprises a biomimetic inner membrane support with a secondary guiding structure and a biomimetic outer membrane support with a double-layer structure. In the nerve conduit with the multistage biomimetic nerve membrane structure, the filler for playing a growth guiding role has a multistage guiding structure, the primary guiding is that cells are directionally migrated along the fiber direction in the directional fiber membrane, are elongated in shape on the fiber and are accelerated in differentiation, and the secondary guiding is that directional microchannels constrain the growth of nerve fibers, promote the maturation of bundling and the alignment of the growth direction. The application solves the problem of insufficient contact guiding efficiency existing in the prior art and overcomes the contradiction between the filling density of guiding fibers, the growth space and the guiding effect.

The invention provides a construction method and device for a brain structure connection atlas, and the method comprises the steps: obtaining a three-dimensional fluorescence microscopic image of brain cells; calculating a response function according to the gradient distribution of the unidirectional fiber groups; according to the gradient weighted sampling data and the response function of each voxel v in the three-dimensional fluorescence microscopic image, constructing a brain structure connection map; the gradient weighted sampling data at each voxel v represents discrete sampling in each direction of the gradient spherical continuous distribution function within a predetermined range near each voxel v. According to the method, the three-dimensional orientation distribution of the white matter nerve fibers of the brain can be obtained through analysis, then the three-dimensional brain structure connection diagram is constructed according to the fiber orientation distribution, and the method has the advantages of being high in speed, high in precision and capable of achieving three-dimensional analysis.

The invention discloses a brain image VR system developed based on unity and blender. The system comprises a nerve fiber direction sensing coloring module, a multi-brain structure model intelligent splitting and memorizing module, a double-data-set layered precise control module, an intelligent profile generation module, a double-end adaptive intelligent slicing module and a customized VR immersive interaction module. The invention further provides a brain image VR method based on unity and blender development. According to the method, the display and rendering efficiency problem of the brain image OBJ model in Unity is effectively solved; the comfort of model observation in the VR scene is improved; and the adaptation stability of the system to different brain image data is ensured.

An endovascular system for targeted photothermal ablation of perivascular nerves is disclosed. A catheter includes a fluid lumen communicating with outlet orifices, and an electromagnetic radiation emitter positioned within a support structure that apposes the array against a vessel wall. A proximal console independently controls irradiation and injection parameters. In use, a nanofluid comprising plasmonic nanoparticles, such as gold nanorods tuned for near-infrared absorption, is injected into or through the vascular wall and subsequently irradiated intraluminally; the nanofluid absorbs energy and converts it to heat to ablate adjacent nerve fibers while reducing non-target tissue heating.

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

The invention discloses a medical clinical image real-time 3D imaging method fused with artificial intelligence, and the method comprises the steps: extracting a basic feature set of original data of a medical clinical image through a real-time 3D image computing power engine, and completing hierarchical feature aggregation through a multi-scale feature aggregation segmentation model to generate a multi-dimensional aggregation feature map, the method comprises the steps of locking focus edge coordinates and drawing an initial contour by means of a focus boundary accurate positioning model, obtaining space correlation data of a focus and a nerve fiber bundle through a nerve fiber bundle three-dimensional tracking algorithm, performing parallel operation, three-dimensional reconstruction and fusion on various types of data by utilizing a real-time 3D image computing power engine, and finally outputting a 3D imaging result through dynamic rendering. And through multi-model collaboration and computing power optimization, full-process intelligentization of feature extraction, focus positioning, structure tracking and imaging output is realized, and the accuracy and real-time performance of imaging are improved.

The present invention is directed inter alia to the treatment of pain. For example, there is provided a chimeric clostridial neurotoxin for use in treating pain by inhibiting the release of a pain mediator from a neuron comprising an Aδ nerve fiber or a C nerve fiber, wherein the chimeric clostridial neurotoxin binds to the neuron comprising the Aδ nerve fiber or the C nerve fiber, respectively, and wherein the chimeric clostridial neurotoxin comprises a botulinum neurotoxin A (BoNT / A) light-chain and translocation domain (HN domain), and a BoNT / B receptor binding domain (HC domain). Also provided are methods, uses, kits, and unit dosage forms.

The invention discloses a wireless implantable nerve electrical stimulation system, and relates to the technical field of medical instruments, and the system comprises an in-vivo implant module and an external alternating magnetic field module. The external alternating magnetic field module is used for acquiring frequency required by nerves; generating a PWM instruction based on the frequency required by the nerve; based on the PWM instruction, a solid-state relay is used for modulating a waveform signal generated by a signal generator; meanwhile, the modulated waveform signal is converted into a discontinuous alternating magnetic field signal; discontinuous alternating magnetic field signals are transmitted; the in-vivo implant module is used for converting a discontinuous alternating magnetic field signal into a discontinuous alternating electric field signal; rectifying the discontinuous alternating electric field signal to obtain a direct current pulse signal; and meanwhile, the direct-current pulse signal is transmitted to the corresponding nerve fiber. According to the invention, efficient and safe electrical stimulation modulation of in-vivo nerves can be realized through wireless energy transmission.

The present invention is directed inter alia to the treatment of pain. For example, there is provided a chimeric clostridial neurotoxin for use in treating pain by inhibiting release of a pain mediator from a neuron comprising an Aδ nerve fiber or a C nerve fiber, wherein the chimeric clostridial neurotoxin binds to the neuron comprising the Aδ nerve fiber or the C nerve fiber, respectively, and wherein the chimeric clostridial neurotoxin comprises a botulinum neurotoxin A (BoNT / A) light-chain and translocation domain (HN domain), and a BoNT / B receptor binding domain (HC domain). Also provided are methods, uses, kits, and unit dosage forms.

Various aspects of this disclosure relate to a layered polymer substrate with electrodes and conductive ink embedded in the substrate. In some embodiments, a prosthetic liner may be bonded onto the polymer substrate. The substrate may include an interconnect coupled to the electrodes via the conductive ink. The system may include a controller (e.g., an electrode controller) in communication with the electrodes via the conductive ink. The electrodes may be activated such that they may stimulate nerve fibers in a user's residual limb.

A method and near-critical argon-based loop catheter for circumferential ablation of nerve fibers are disclosed. According to one aspect, cryogenic catheter is configured to deliver near-critical-temperature argon cooling fluid to ablate parasympathetic innervation in nerve fibers in a wall of a passageway within a patient into which a distal portion of the cryogenic catheter is inserted, the passageway being one of an air passageway of a lung and a blood passageway. The cryogenic catheter includes at least one shaft to deliver argon cooling fluid to at least one expandable treatment element at the distal portion of the cryogenic catheter, an expandable treatment element being biased to form a multiple loop coil structure when expanded to make circumferential contact with the wall of the passageway. The cryogenic catheter also includes at least one expandable treatment element configured to be expandable by at least one of fluid pressure and mechanical force applied to a push wire within the shaft.

A system for controlling selective stimulation of neural tissue of a subject is provided. Said system comprises a first electrode arrangement, comprising a plurality of electrodes, configured to be arranged in in relation to a first longitudinal position of the neural tissue, a second electrode arrangement, comprising at least one electrode and configured to be arranged at a second longitudinal position of the neural tissue, and a stimulation signal generating unit. The stimulation signal generating unit is configured to generate a first intermittent current waveform comprising a first pulse and a second intermittent current waveform comprising a second pulse, for causing interferential stimulation of a plurality of nerve fibers of the neural tissue. The stimulation signal generating unit is further configured to generate and output a blocking pulse to the second electrode arrangement, for temporally selectively blocking propagation of signals through the neural tissue at the second longitudinal position.

The invention provides a cranial nerve fiber bundle labeling method and device, electronic equipment and a readable storage medium, and relates to the technical field of image processing.The cranial nerve fiber bundle labeling method comprises the steps that original spectrograph imaging data containing a brain image is collected, and the original spectrograph imaging data is solved to obtain an intensity image and a phase delay image; respectively determining to-be-labeled data in the intensity image and the phase delay image after noise reduction preprocessing, segmenting the to-be-labeled phase delay image based on a coarse segmentation threshold value obtained through pre-calculation to obtain a coarse segmentation mask, and on the basis of an initial brain nerve fiber bundle form determined by the coarse segmentation mask, marking the to-be-labeled data in the intensity image and the to-be-labeled data in the phase delay image; obtaining labeling results of the brain nerve fiber bundle of the to-be-labeled intensity image of different users, and storing the labeling results under the condition that similarities among different labeling results of all labeling layers in the labeling layer range are greater than a specified threshold value; and the cranial nerve fiber bundle can be positioned and labeled more accurately by utilizing complementarity information of the intensity image and the phase delay image.

The invention discloses a retina nerve fiber layer defect analysis method based on an eye fundus image, and relates to the technical field of retina nerve fiber layer image recognition and analysis. The technical defects that fiber defects of a retina nerve fiber layer are high in cost, analysis depends on experience, and quantization and accurate classification capacity is lacked are overcome. The method comprises the steps that 1, image data are acquired; the method comprises the following steps: acquiring an eye fundus image of a retina nerve fiber layer through an eye fundus camera, acquiring first scale image data, acquiring second scale image data of which the pixel value is greater than that of the first scale image data, and marking a nerve fiber most concentrated area on the second scale image; 2, generating a dual-scale supervision signal; step 3, data enhancement processing; 4, constructing a multi-task deep learning model; step 5, defect classification; the feature map is converted into a feature vector through a global average pooling layer, and then a classification prediction result is obtained through two full connection layers. The problem of dependence on subjective experience of doctors is effectively solved, and the diagnosis efficiency is improved.

The present invention discloses a method, device and equipment for identifying retinal nerve fiber layer defects, wherein the method includes: obtaining an eye image to be identified, including: retinal nerve fiber layer information; performing image recognition on the eye image to be identified based on the retinal nerve fiber layer information to obtain a first identification area, the first identification area including at least two first feature points, each first feature point being used to characterize a retinal nerve fiber defect starting point; selecting any first feature point for parameter configuration to obtain an identification feature; based on the identification feature, performing sub-feature identification on the at least two first feature points respectively to obtain at least two sub-feature curves, each sub-feature curve being used to characterize the area of ​​retinal nerve fiber defects corresponding to the first feature point; obtaining a target identification area based on the at least two sub-feature curves, the target identification area being the retinal nerve fiber layer defect area. In the above manner, the present invention improves labeling efficiency and quality.

Various aspects of this disclosure relate to a layered polymer substrate with electrodes and conductive ink embedded in the substrate. In some embodiments, a prosthetic liner may be bonded onto the polymer substrate. The substrate may include an interconnect coupled to the electrodes via the conductive ink. The system may include a controller (e.g., an electrode controller) in communication with the electrodes via the conductive ink. The electrodes may be activated such that they may stimulate nerve fibers in a user's residual limb.

The application discloses a multifunctional underwater sensing fiber bionic nerve hillock cell receptor and a preparation method, and belongs to the field of bionic artificial receptors. The bionic nerve hillock cell receptor comprises a bionic nerve fiber, a first reflecting surface, a bionic supporting cell, a second reflecting surface, a bionic sensory hair cell and a bionic gel cap. The bionic nerve fiber is used for transmitting input light signals and output light signals. The bionic supporting cell is used for supporting the bionic sensory hair cell and the bionic gel cap, and forms a Fabry-Perot cavity together with the first reflecting surface and the second reflecting surface. The bionic sensory hair cell comprises one moving cilium and a plurality of non-moving cilia. The bionic gel cap contains bionic gel material, has viscous resistance and friction, and is used for wrapping the bionic sensory hair cell. The application solves the problems of poor biocompatibility, large volume, poor directivity and single function of the bionic receptor in the prior art.

The invention relates to the technical field of visual impairment simulation, in particular to a visual impairment dynamic evolution simulation system and method. Multi-modal medical image data of a patient is collected and subjected to preprocessing and focus positioning, an individual visual pathway fiber bundle is constructed by adopting a deterministic fiber tracking algorithm based on diffusion tensor imaging data, non-rigid registration is performed on the individual fiber bundle and a standard visual pathway template, a local deformation field is calculated, and the focus positioning accuracy is improved. Based on a local deformation field, analyzing a spatial geometrical relationship between a focus mask and each section of nerve fiber to obtain an individualized three-dimensional visual pathway model and an SDI scoring matrix of each section corresponding to the individualized three-dimensional visual pathway model, and judging a damaged pathway section and a typical visual field defect mode matched with the damaged pathway section in degree; according to the method, individualized visual simulation of a patient is realized, a visual dynamic evolution prediction model is constructed by utilizing diffusion Transform, and dynamic evolution of visual impairment is realized.