Nerve fiber screening method and related apparatus

Abstract

A nerve fiber screening method and a related apparatus. The nerve fiber screening method comprises: acquiring medical image data of a patient, wherein the medical image data comprises nerve fiber data and nucleus data (S1); on the basis of the nerve fiber data and the nucleus data, determining an association relationship between a nucleus and nerve fibers (S2); and on the basis of a screening target and the association relationship between the nucleus and the nerve fibers, determining at least one target nerve fiber (S3).

Description

Method and related device for screening nerve fibers

[0001] This application claims priority to the Chinese patent application No. 202410837112.6, filed on June 26, 2024, with the Chinese Patent Office, the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the technical field of nerve fiber screening, for example, to a method and related device for screening nerve fibers. BACKGROUND

[0003] In neuroscience research and clinical applications, accurate screening and analysis of nerve fibers are crucial for understanding the distribution and connection of brain fibers. However, nerve fiber screening methods often face many challenges.

[0004] Firstly, the distribution of nerve fibers in the brain is extremely complex and large in number, which leads to visual confusion and occlusion problems when displaying and tracking nerve fibers in three-dimensional space. This makes it difficult for doctors to directly observe the overall structure and connection of nerve fibers, thereby limiting the doctor's ability to analyze and judge the whole brain fibers in depth.

[0005] Secondly, with the continuous development of electrical pulse stimulation programming technology (such as deep brain stimulation system), doctors need to be able to adjust the parameters of the stimulator to optimize the treatment effect of patients. In visual programming, doctors need to clearly see the patient's brain nuclei, implanted electrodes, and three-dimensional (3D) model of nerve fibers. However, due to the density and chaos of nerve fibers, the nerve fibers that play a conductive role are often difficult to display individually, increasing the difficulty of analysis and judgment for doctors.

[0006] Although some nerve fiber screening methods, such as those based on the direction of nerve fibers, can help doctors screen nerve fibers to some extent, these methods cannot directly screen nerve fibers that play a conductive role when stimulating specific nuclei (such as pre-set nuclei), thus limiting their application in clinical scenarios such as visual programming. SUMMARY

[0007] The present application provides a method and related device for screening nerve fibers that play a conductive role when stimulating specific nuclei (such as pre-set nuclei).

[0008] The present application adopts the following technical solutions:

[0009] The present application provides a method for screening nerve fibers, comprising:

[0010] obtaining medical image data of a patient, the medical image data comprising nerve fiber data and nucleus data;

[0011] determining, according to the nerve fiber data and the nucleus data, a correlation between the nuclei and the nerve fibers;

[0012] determining, according to a screening target and the correlation between the nuclei and the nerve fibers, at least one target nerve fiber.

[0013] In one or more embodiments, the correlation between the nuclei and the nerve fibers comprises:

[0014] a positional relationship between any nucleus and any nerve fiber, the positional relationship comprising at least that the nerve fiber links the nucleus or the nerve fiber does not link the nucleus.

[0015] In one or more embodiments, the determining, according to the nerve fiber data and the nucleus data, a correlation between the nuclei and the nerve fibers comprises:

[0016] determining, respectively according to the nerve fiber data and the nucleus data, a nerve fiber model and a nucleus model of the brain of the patient;

[0017] determining, according to a positional relationship of each nerve fiber model and each nucleus model in the brain of the patient, a correlation between the nuclei and the nerve fibers.

[0018] In one or more embodiments, the determining, according to a positional relationship of each nerve fiber model and each nucleus model in the brain of the patient, a correlation between the nuclei and the nerve fibers comprises:

[0019] placing each nerve fiber model and each nucleus model in a three-dimensional simulation environment of the brain of the patient to determine a three-dimensional model of the brain of the patient;

[0020] determining, according to the three-dimensional model of the brain of the patient, a spatial position of each nerve fiber model and each nucleus model in the brain of the patient, and determining, based on the spatial position, a correlation between the nuclei and the nerve fibers.

[0021] In one or more embodiments, the determining, according to a positional relationship of each nerve fiber model and each nucleus model in the brain of the patient, a correlation between the nuclei and the nerve fibers comprises:

[0022] placing each nerve fiber model and each nucleus model in a three-dimensional simulation environment of the brain of the patient to determine a three-dimensional model of the brain of the patient;

[0023] extending from any point on any nerve fiber in the nerve fiber model in the three-dimensional model in any direction to obtain an extension line;

[0024] According to the intersection relationship between the extension line and the nuclei in the nuclei model in the three-dimensional model, the association relationship between the nerve fiber and the nuclei is determined.

[0025] In one or more embodiments, according to the intersection relationship between the extension line and the nuclei in the nuclei model in the three-dimensional model, the association relationship between the nerve fiber and the nuclei is determined, comprising:

[0026] If the extension line intersects with at least one nuclei and has only one intersection point with the at least one nuclei, the nerve fiber is characterized by linking the nuclei; and / or,

[0027] If the extension line intersects with at least one nuclei and has two intersection points with the at least one nuclei, the nerve fiber does not link the nuclei.

[0028] In one or more embodiments, the nerve fiber data comprises sample point coordinates of nerve fibers, the sample point coordinates comprising an identification of the nerve fibers, the identification of each nerve fiber being different, and the nuclei data comprising model data of each nuclei in the brain of the patient;

[0029] The nerve fiber model and the nuclei model of the brain of the patient are determined according to the nerve fiber data and the nuclei data, respectively, comprising:

[0030] The sample point coordinates with the same identification are clustered to obtain a sample point coordinate set corresponding to the nerve fiber;

[0031] The sample point coordinates in each sample point coordinate set are concatenated to obtain a nerve fiber model corresponding to each sample point coordinate set in the brain of the patient;

[0032] According to the model data of each nuclei in the brain of the patient, a nuclei model of the brain of the patient is generated.

[0033] In one or more embodiments, the nerve fiber linking the nuclei comprises:

[0034] The end of the nerve fiber is located inside the nuclei, or the nerve fiber passes through the nuclei.

[0035] In one or more embodiments, the screening target comprises at least one preset nuclei and a nerve fiber in a target association relationship with the preset nuclei.

[0036] In one or more embodiments, the preset nuclei comprises a target nuclei and / or a non-target nuclei;

[0037] The target association relationship comprises:

[0038] a nerve fiber linking at least one target nuclei, or

[0039] neural fibers linking at least one target nucleus and not linking at least one non-target nucleus.

[0040] neural fibers linking at least one target nucleus and not linking at least one non-target nucleus.

[0041] In one or more embodiments, the screening method of neural fibers further comprises:

[0042] acquiring display information for the target neural fibers;

[0043] loading a three-dimensional model of the patient's brain into a display screen and rendering the target neural fibers in the three-dimensional model of the patient's brain through the display information to display the target neural fibers through the display screen.

[0044] The present application also provides a screening device of neural fibers, comprising:

[0045] an acquiring module configured to acquire medical image data of a patient, the medical image data comprising neural fiber data and nucleus data;

[0046] an associating module configured to determine an association between the nucleus and the neural fiber according to the neural fiber data and the nucleus data;

[0047] a target neural module configured to determine at least one target neural fiber according to a screening target and the association between the nucleus and the neural fiber.

[0048] In one or more embodiments, the associating module comprises:

[0049] a neural fiber submodule configured to cluster sampling point coordinates with the same identifier to obtain a sampling point coordinate set of a corresponding neural fiber, and concatenate the sampling point coordinates in each sampling point coordinate set to obtain a neural fiber model corresponding to each sampling point coordinate set in the patient's brain;

[0050] a nucleus submodule configured to generate a nucleus model of the patient's brain according to model data of each nucleus in the patient's brain;

[0051] a three-dimensional model submodule configured to place each neural fiber model and each nucleus model in a three-dimensional simulation environment of the patient's brain to determine a three-dimensional model of the patient's brain;

[0052] an extension line submodule configured to extend from any point on any neural fiber in the neural fiber model in the three-dimensional model in any direction to obtain an extension line;

[0053] The association submodule is configured to determine the association between the neural fiber and the nucleus according to the intersection relationship between the extension line and the nucleus in the nucleus model in the three-dimensional model.

[0054] In one or more embodiments, the target neural module includes:

[0055] The preset nucleus submodule includes a plurality of preset nucleus units configured to set the preset nucleus.

[0056] The preset relationship submodule includes a plurality of preset position units configured to set the position relationship between the preset nucleus and the target neural fiber.

[0057] The target submodule is configured to form the target neural fiber according to the plurality of preset nucleus units, the plurality of preset position units, and the signal of the position module.

[0058] The visualization submodule is configured to display the target neural fiber formed by the target submodule.

[0059] The present application also provides a medical device including a processor, a memory, and a computer program stored on the memory, wherein the processor executes the computer program to implement the screening method of the neural fiber.

[0060] The present application also provides a computer readable storage medium having a computer program / instruction stored thereon, wherein the computer program / instruction is executed by a processor to implement the screening method of the neural fiber.

[0061] The present application also provides a computer program product including a computer program / instruction, wherein the computer program / instruction is executed by a processor to implement the screening method of the neural fiber. BRIEF DESCRIPTION OF DRAWINGS

[0062] FIG. 1 is a flowchart of a screening method of a neural fiber according to an embodiment of the present application.

[0063] FIG. 2 is a flowchart of a screening method of a neural fiber according to an embodiment of the present application.

[0064] FIG. 3 is a structural schematic diagram of a screening device of a neural fiber according to an embodiment of the present application.

[0065] FIG. 4 is a structural schematic diagram of a target neural fiber (left nucleus accumbens) according to an embodiment of the present application.

[0066] FIG. 5 is a structural schematic diagram of a complete neural fiber according to an embodiment of the present application. DETAILED DESCRIPTION

[0067] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations, however, can be implemented in many different forms and should not be construed as limited to the implementations set forth herein.

[0068] Below, one of the application fields of the embodiments of the present application (i.e., implantable devices) will be briefly described. An implantable neurostimulation system (a kind of implantable medical system) mainly includes a stimulator implanted in a patient's body and a programming device arranged outside the patient's body. The neuroregulation technology mainly implants an electrode in a specific structure (i.e., a target point) in the body through stereotactic surgery, and delivers an electric pulse to the target point by the stimulator implanted in the patient's body through the electrode, so as to regulate the electrical activity and function of the corresponding nerve structure and network, thereby improving symptoms and relieving pain. Among them, the stimulator can be any one of an implantable neuroelectric stimulation device, an implantable cardiac electric stimulation system (also known as a cardiac pacemaker), an implantable drug delivery device (IDDS), and a lead adapter device. The implantable neuroelectric stimulation device is, for example, a deep brain stimulation (DBS) system, an implantable cortical nerve stimulation (CNS) system, an implantable spinal cord stimulation (SCS) system, an implantable sacral nerve stimulation (SNS) system, an implantable vagus nerve stimulation (VNS) system, etc.

[0069] In some embodiments, the stimulator can include an implantable pulse generator (IPG), an electrode lead, and an extension lead arranged between the implantable pulse generator and the electrode lead, and the data interaction between the implantable pulse generator and the electrode lead is realized through the extension lead. The implantable pulse generator is arranged in the patient's body. In response to the programming instructions sent by the programming device, the sealed battery and the circuit provide controllable electric stimulation energy to the tissue in the body, and through the implanted extension lead and electrode lead, one or two controllable specific electric stimulations are delivered to the specific region of the tissue in the body. The extension lead is used in cooperation with the implantable pulse generator as a transmission medium of the electric stimulation signal, and the electric stimulation signal generated by the implantable pulse generator is transmitted to the electrode lead. The electrode lead delivers the electric stimulation to the specific region of the tissue in the body through the electrode contacts thereon. The stimulator is provided with single-sided or double-sided one or more electrode leads, and a plurality of electrode contacts are arranged on the electrode lead.

[0070] In other embodiments, the stimulator can only include the pulse generator and the electrode lead. In this case, the pulse generator can be embedded on the skull of the patient, and the electrode lead is implanted in the brain of the patient, and the pulse generator is directly connected to the electrode lead without the need of an extension lead.

[0071] The electrode lead can be a neurostimulation electrode, and the electrode lead delivers electrical stimulation to a specific region of the body tissue through a plurality of electrode contacts. The stimulator is provided with one or more electrode leads, and the electrode lead is provided with a plurality of electrode contacts, which can be arranged uniformly or non-uniformly in the circumferential direction of the electrode lead. As an example, the electrode contacts can be arranged in a 4-row 3-column array (a total of 12 electrode contacts) in the circumferential direction of the electrode lead. The electrode contacts can include stimulation contacts and / or collection contacts. The electrode contacts can have a sheet shape, a ring shape, a dot shape, etc.

[0072] In some possible manners, the body tissue to be stimulated can be the brain tissue of the patient, and the stimulation site can be a specific site of the brain tissue. When the type of the disease of the patient is different, the stimulation site is generally different, and the number of stimulation contacts (single source or multiple sources) used, the use of one or more specific electrical stimulation signals (single channel or multiple channels), and the stimulation parameter data are also different. It can be considered that when the stimulation contacts used are multiple sources and multiple channels (multiple channels), a larger amount of data will be generated compared to single source and single channel.

[0073] The embodiments of the present application are not limited to the type of disease to be treated, and can be used for DBS, SCS, pelvic stimulation, gastric stimulation, peripheral nerve stimulation, functional electrical stimulation, etc. The types of diseases that can be treated by DBS include: convulsive diseases (e.g., epilepsy), pain, migraine, mental diseases (e.g., major depressive disorder (MDD)), bipolar disorder, anxiety disorder, post-traumatic stress disorder, dysthymia, obsessive-compulsive disorder (OCD), behavioral disorders, emotional disorders, memory disorders, mental state disorders, movement disorders (e.g., essential tremor or Parkinson's disease), Huntington's disease, Alzheimer's disease, drug addiction, autism, or other neurological or psychiatric diseases and injuries.

[0074] The stimulation parameters can include one or more of a frequency (e.g., number of electrical stimulation pulse signals per unit time 1s, in Hz), a pulse width (duration of each pulse, in ps), an amplitude (intensity of each pulse, typically expressed in voltage, in V), a timing (e.g., continuous or triggered), a stimulation mode (including one or more of a current mode, a voltage mode, a timed stimulation mode, and a cyclic stimulation mode), a physician control upper and lower limit (range adjustable by a physician), and a patient control upper and lower limit (range adjustable by a patient).

[0075] When stimulating a certain nucleus, the electrical stimulation can be conducted along the nerve fibers to other brain regions, affecting other parts of the brain. In order to screen the nerve fibers (e.g., target nerve fibers) that play a conducting role when stimulating a specific nucleus (e.g., a preset nucleus), the present application introduces a nerve fiber screening method and related device.

[0076] Referring to FIG. 1, the nerve fiber screening method of the present application includes steps S1-S3.

[0077] Step S1: Obtain medical image data of a patient, the medical image data including nerve fiber data and nucleus data.

[0078] The nerve fiber data includes sampling point coordinates of the nerve fibers, and the sampling point coordinates include an identification of each nerve fiber, and the nucleus data includes model data of each nucleus in the brain of the patient.

[0079] Exemplarily, taking the brain of a patient as an example, the nerve fiber data can include coordinates (i.e., sampling point coordinates) of multiple positions on each nerve fiber obtained by analyzing medical images of the brain of the patient, where the medical images can be X-ray images, computed tomography (CT) images, nuclear magnetic resonance images, ultrasound images, etc., and the type of image is not limited.

[0080] In order to facilitate quick and accurate identification of each nerve fiber, each sampling point coordinate can further include an identification of the nerve fiber, which can be set in advance by a person, such as taking a three-dimensional coordinate system as an example, the sampling point coordinate can be [x, y, z, s], where x is the horizontal coordinate of the sampling point of the nerve fiber, y is the vertical coordinate of the sampling point of the nerve fiber, z is the vertical coordinate of the sampling point of the nerve fiber, and s is the identification of the nerve fiber. In this way, the value of s of the sampling points at different positions on each nerve fiber is consistent. In some other embodiments, the sampling point coordinates can also be other coordinate identification forms, which are not limited in the embodiments of the present application.

[0081] The sampling points of each nerve fiber can at least include coordinates of two end points of the nerve fiber, so that when the model of the nerve fiber is restored through the sampling points, the entire nerve fiber can be directly restored. Generally, the extension direction of the nerve fiber is not a straight line, and therefore a plurality of sampling points can be collected at a middle position of the nerve fiber, so that the model of the nerve fiber can be accurately restored through the plurality of sampling points. Optionally, for a nerve fiber with a large bending degree, a larger number of sampling points can be collected, that is, the number of sampling points to be collected can be determined according to the bending degree of the nerve fiber.

[0082] The model data of the nucleus can be coordinate points at different positions of the nucleus. Since the nucleus is an irregular brain tissue, more coordinate points need to be collected to reliably and accurately restore the nucleus. The model data can also be other forms of data.

[0083] Optionally, the relevant nucleus set can be determined according to the patient's disease information, so that only the model data of the nucleus set needs to be obtained, thereby reducing the amount of data obtained and improving the processing capacity and efficiency of subsequent data. For example, for Parkinson's disease, the relevant nuclei can include the nucleus accumbens, the subthalamic nucleus, the ventral intermediate nucleus, the medial globus pallidus, the internal capsule, and the ventral striatum.

[0084] Step S2: determining the association relationship between the nuclei and the nerve fibers according to the obtained nerve fiber data and nucleus data.

[0085] It can be understood that in the brain environment of the patient, there are a large number of nerve fibers and nuclei. The nerve fibers serve as a medium for transmitting signals, substances or instructions, and are used to link and transmit relevant information to the nuclei. There is a certain relationship between different nerve fibers and nuclei. Therefore, the morphology of the nerve fibers and the nuclei in the brain can be restored through the nerve fiber data of the patient's brain, so that the association relationship between each nucleus and each nerve fiber can be determined through the actual positional relationship between the nuclei and the nerve fibers.

[0086] The association relationship can be a transmission relationship between the nuclei and the nerve fibers. In an objective state, it can be a positional relationship between the nuclei and the nerve fibers, that is, when the nerve fibers are linked to the nuclei, the nerve fibers can transmit relevant information to the nuclei; when not linked, there is no transmission relationship between the two. In this way, the set of nerve fibers related to each nucleus in the patient's brain or the set of nuclei in the transmission direction of each nerve fiber can be determined, thereby improving the reliability of subsequent nerve fiber screening.

[0087] In the embodiments of the present specification, step S2 includes steps S21-S22 to introduce how to determine the association relationship between the nuclei and the nerve fibers, as shown in FIG. 2.

[0088] Step S21: determining a nerve fiber model and a nucleus model of the brain of the patient according to the nerve fiber data and the nucleus data respectively.

[0089] In step S21, the nerve fiber model of the brain of the patient is extracted and reconstructed from the medical image data by image processing techniques and three-dimensional reconstruction algorithms using the obtained nerve fiber data. In application, the nerve fiber data can include the coordinates, diameter, direction, and other information of the sampling points of the nerve fibers. Similarly, the nucleus model of the brain of the patient can be constructed using the nucleus data. In application, the nucleus data can include the shape, size, position, and other characteristics of the nuclei.

[0090] In the embodiments of the present specification, step S21 includes steps S211-S213 to introduce how to determine the nerve fiber model and the nucleus model.

[0091] Step S211: clustering the coordinates of the sampling points with the same identifier to obtain a corresponding set of coordinates of the sampling points of the nerve fiber.

[0092] In the medical image data of the nerve fibers, the nerve fibers can be represented by a series of sampling point coordinates, which contain the identifier information of the nerve fibers to distinguish different nerve fibers.

[0093] In application, all the coordinates of the sampling points with the same identifier are first identified, which belong to the same nerve fiber. The clustering algorithm (for example, K-means clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, etc.) is used to gather the coordinates of the sampling points with the same identifier together to form a set of coordinates of the sampling points, which represents the position and shape of the nerve fiber in the three-dimensional space and can be used for subsequent construction of the nerve fiber model.

[0094] In addition, the clustering process can effectively organize a large number of scattered sampling point coordinates to form a nerve fiber model with clear structure and shape, which is helpful for subsequent analysis of the correlation between the nerve fiber and the nucleus.

[0095] Step S212: concatenating the coordinates of the sampling points in each set of coordinates of the sampling points to obtain the nerve fiber model corresponding to each set of coordinates of the sampling points in the brain of the patient.

[0096] Determine the order of the plurality of sampling points in the set of sampling point coordinates. In application, the order can be determined according to the orientation of the neural fiber and the acquisition method of the medical image data. For example, in magnetic resonance imaging (MRI) or CT images, the sampling points are usually arranged in the order of the scanned layers or time sequence. According to the determined order, the sampling point coordinates are connected in sequence, and the connecting lines between them constitute the basic shape of the neural fiber. In order to improve the accuracy and visualization effect of the model, the neural fiber after connection can be smoothed. In application, this can be achieved through interpolation algorithms (such as linear interpolation, spline interpolation, etc.) to increase the point density on the neural fiber path, making the model smoother and more continuous. After the construction is completed, the neural fiber model can be verified to ensure its accuracy and integrity. In application, this can be done by comparing the verification results with the original medical image data, analyzing the geometric characteristics of the model, etc.

[0097] Step S213: generating a nucleus model of the patient's brain according to the model data of each nucleus in the patient's brain.

[0098] The present application can accurately generate neural fiber models and nucleus models from sampling point coordinates, improving the accuracy and efficiency of model generation.

[0099] In step S213, generating a nucleus model of the patient's brain according to the model data of each nucleus in the patient's brain usually involves processing and analyzing medical image data to extract the shape, size, location, and other characteristics of the nucleus.

[0100] In some embodiments, the medical digital imaging and communications (DICOM) image data of the user (patient) can be analyzed by using professional software, such as DSI-Studio. DSI-Studio can analyze the diffusion tensor imaging (DTI) or diffusion spectrum imaging (DSI) data in the DICOM data, generate the coordinates of the neural fibers, and write the generated coordinates into a txt document, which records all the coordinate points constituting each neural fiber. According to the discrete coordinate data of each neural fiber in the txt document, a plurality of curves are connected, each curve being a neural fiber, and thus a neural fiber model is obtained. In some embodiments, the DICOM image of the patient can be imported into professional software, such as 3Dslicer. 3Dslicer is an open-source medical image processing and analysis software that supports multiple medical image formats, including DICOM. Through the data analysis function of 3Dslicer, the model data of the nuclei can be extracted from the DICOM data, and a nuclei model file in the polygon file format (PLY) can be generated. PLY is a polygon file format that can be used to represent a three-dimensional model structure. In the PLY file, all the coordinate points constituting each nucleus are recorded, and these discrete coordinate data are connected to form a plurality of areas, each area representing a nucleus. In addition, the shape of each area reflects the actual shape of the nucleus, such as caudate, lentiform, or other shapes. According to the model data of each nucleus in the patient's brain in the nuclei model file, a nuclei model of the patient's brain is generated.

[0101] Step S22: determining the association between the nuclei and the neural fibers according to the positional relationship between each neural fiber model and each nuclei model in the patient's brain.

[0102] The present application helps to more intuitively understand the spatial relationship between the neural fibers and the nuclei by establishing models to simulate the structure of the patient's brain.

[0103] In step S22, the constructed nerve fiber model and the nucleus model are placed in the same three-dimensional space, i.e., the three-dimensional simulation environment of the patient's brain. By comparing the positional relationship of each nerve fiber model and each nucleus model in the three-dimensional space, the association relationship between the nerve fiber and the nucleus can be accurately determined. Whether the nerve fiber is linked to the nucleus can be determined by calculating the distance, angle, and other parameters between the nerve fiber model and the nucleus model. For example, if one end or part of the nerve fiber model is located inside the nucleus model, or the nerve fiber model intersects with the nucleus model, it can be considered that the nerve fiber is linked to the nucleus. In addition, the association degree between the nerve fiber and the nucleus can be further determined according to the direction of the nerve fiber and the positional relationship of the nucleus. For example, if the direction of the nerve fiber points to the nucleus, or the distance between the nerve fiber and the nucleus is close, it can be considered that there is a strong association relationship between the nerve fiber and the nucleus.

[0104] In the embodiments of the present application, step S22 includes steps S221-S222 to introduce how to determine the association relationship between the nucleus and the nerve fiber.

[0105] Step S221: Place each nerve fiber model and each nucleus model in the three-dimensional simulation environment of the patient's brain to determine the three-dimensional model of the patient's brain, as shown in FIG. 5. When applied, the three-dimensional simulation environment is constructed based on the medical image data of the patient's brain, which can accurately reflect the structure and morphology of the patient's brain, and thus an accurate three-dimensional model of the patient's brain can be obtained.

[0106] In other embodiments, a professional graphics rendering engine, such as THREE.JS, can be used to directly render the PLY format nucleus model file in a 3D scene. At the same time, the nerve fiber can also be rendered into the same 3D scene, thereby obtaining a complete nerve fiber rendering 3D graph simulating the internal structure of the human brain, i.e., the three-dimensional model of the patient's brain.

[0107] Step S222: Determine the spatial position of each nerve fiber model and each nucleus model in the patient's brain based on the three-dimensional model of the patient's brain, and determine the association relationship between the nucleus and the nerve fiber based on the spatial position.

[0108] The present application can intuitively display the spatial positional relationship of the nerve fiber and the nucleus through the three-dimensional simulation environment, making the determination of the association relationship more intuitive and accurate.

[0109] In the three-dimensional simulation environment of the patient's brain that has been constructed, each nerve fiber model and each nucleus model has specific location information. The location information can be in the form of three-dimensional coordinates, which can accurately determine the location of each nerve fiber model and each nucleus model in the patient's brain. Using professional medical image processing software or custom algorithms, the three-dimensional coordinates of each nerve fiber model and nucleus model are extracted and accurately positioned in three-dimensional space.

[0110] After determining the spatial positions of nerve fibers and nuclei, the relationship between nerve fibers and nuclei can be further analyzed based on factors such as their relative positions, distances, directions, etc. For example, if one end or part of a nerve fiber is located inside or near a certain nucleus, or the distance between the nerve fiber and the nucleus is within a medically meaningful range, then the nerve fiber can be considered to be associated with the nucleus. Similarly, if the direction of the nerve fiber points to a certain nucleus, or the angle between them is small, it can also be used as a basis for determining their association. After determining the association between nerve fibers and nuclei, the degree of this association can be further quantified. This can be achieved by calculating parameters such as distance, angle, overlap, etc. between them. For example, the Euclidean distance can be used to calculate the straight-line distance between the nerve fiber and the nucleus, or the cosine of the angle can be used to measure the directional similarity between them, in order to more accurately assess the degree of association between the nerve fiber and the nucleus.

[0111] In the embodiments of the present specification, step S222 includes steps S2221-S2222 to introduce how to determine the association between nuclei and nerve fibers.

[0112] Step S2221: extending a line from any point on any nerve fiber model in the three-dimensional model in any direction.

[0113] In the nerve fiber model in the three-dimensional model, a point is randomly or according to a certain rule. The point can be located at any position of the nerve fiber, including the head end, the tail end or a certain point in the middle. Determine the extension direction from this point. In order to be comprehensive and accurate in analysis, multiple different directions can be selected for extension. The direction can be arbitrary, for example: it can be along the direction of the nerve fiber, perpendicular to the direction of the nerve fiber or at a certain angle to the nerve fiber. After determining the extension point and the extension direction, a straight line or a ray is generated by extending from the selected point in the determined direction. In actual operation, in order to facilitate calculation and visualization needs, the extension line is usually limited to a certain length range.

[0114] Step S2222: determining the association relationship between the neural fiber and the nucleus in the three-dimensional model according to the intersection relationship between the extension line and the nucleus in the nucleus model. The association relationship between the nucleus and the neural fiber includes the positional relationship between any nucleus and any neural fiber, which at least includes the neural fiber linking the nucleus or the neural fiber not linking the nucleus.

[0115] The application can clearly determine the positional relationship between the neural fiber and the nucleus, provide specific and reliable basis for screening the target neural fiber, and improve the accuracy and efficiency of the screening.

[0116] The application uses the intersection relationship between the extension line and the nucleus to simply and quickly determine whether the neural fiber links the nucleus, and improves the efficiency and accuracy of the association relationship determination.

[0117] After the extension line is generated, the relationship between the extension line and the nucleus model is further analyzed, for example, the intersection relationship between the extension line and the nucleus model is determined by calculating the intersection point between the extension line and the boundary of the nucleus model. For example, (1) single intersection point: if the extension line intersects with at least one nucleus and there is only one intersection point, it can be considered that the neural fiber at least links the nucleus. The link includes two possible cases: one is that the end (the head end or the tail end) of the neural fiber is located inside the nucleus, which means that the neural fiber is directly linked to the nucleus; the other is that the neural fiber passes through the nucleus, which means that the neural fiber has a path inside the nucleus. The head end can be regarded as the end of the neural fiber connected to the neuron cell body, that is, the starting point of the axon or dendrite extending from the neuron cell body, that is, the starting point of the nerve impulse; the tail end is the end of the neural fiber, that is, the nerve ending, which is distributed in various organs and tissues, and is the terminal structure of the neural fiber, which is responsible for transmitting nerve impulses to other cells or tissues, or receiving nerve impulses from other cells or tissues. (2) Multiple intersection points: if the extension line intersects with at least one nucleus and there are two or more intersection points, it can be considered that the neural fiber does not link the nucleus. Because multiple intersection points mean that the extension line intersects with the boundary of the nucleus outside the nucleus, rather than passing through the nucleus inside or directly linking the nucleus. As can be seen, the application determines the positional relationship between the neural fiber and the nucleus by using the extension line, which makes the operation process more simple and intuitive, and doctors can quickly determine the association relationship between the neural fiber and the nucleus by checking the intersection relationship between the extension line and the nucleus, thereby reducing the operation difficulty and error rate. The application clearly defines two cases of the neural fiber linking the nucleus, i.e., the end is located inside the nucleus or the neural fiber passes through the nucleus, which helps to more accurately identify the path of the neural fiber and provides a clear judgment standard for determining the association relationship between the neural fiber and the nucleus.

[0118] determining the association between the nerve fiber and the nucleus according to the intersection relationship between the extension line and the nucleus in the nucleus model in the three-dimensional model, comprising:

[0119] if the extension line intersects with at least one nucleus and has only one intersection point with the at least one nucleus, the nerve fiber is characterized by linking the at least one nucleus; and / or,

[0120] if the extension line intersects with at least one nucleus and has two intersection points with the at least one nucleus, the nerve fiber does not link the at least one nucleus.

[0121] The present application can clearly determine whether the nerve fiber links the nucleus by specific judgment conditions (for example, the number of intersection points between the extension line and the nucleus), and provides a more accurate basis for screening the target nerve fiber.

[0122] Step S3: determining at least one target nerve fiber according to the screening target and the association between the nucleus and the nerve fiber.

[0123] The present application can accurately and quickly determine the target nerve fiber by obtaining the medical image data of the patient, in particular the data of the nerve fiber and the nucleus, and provides an important diagnostic basis for doctors, which is helpful for accurate treatment of neurological diseases.

[0124] After the association between the nerve fiber and the nucleus is analyzed, step S3 is entered, and the doctor needs to determine the screening target. The screening target can include finding a nerve fiber directly linked to a specific nucleus, finding a nerve fiber passing through a specific region, or finding a nerve fiber related to a specific disease, etc. The screening target of the embodiment of the present application includes at least one preset nucleus and a nerve fiber in a target association relationship with the preset nucleus. The present application can selectively screen the target nerve fiber related to a specific disease or pathology by the preset nucleus and the nerve fiber in the target association relationship with the nucleus, and provides important help for diagnosis and treatment of diseases.

[0125] The preset nucleus includes a target nucleus and / or a non-target nucleus. The target association relationship includes a nerve fiber linking or only linking at least one target nucleus, or a nerve fiber not linking at least one non-target nucleus, or a nerve fiber linking or only linking at least one target nucleus and not linking at least one non-target nucleus. The present application further classifies the preset nucleus and the target association relationship, and makes the screening process more accurate.

[0126] Using the association between the nerve fibers and the nuclei determined in step S222, in particular, the positional relationship (e.g., linked relationship, unlinked relationship, etc.) therebetween, the nerve fibers that meet the doctor's screening target are screened out. Based on the doctor's screening target and the analysis of the association, at least one target nerve fiber will be determined. The target nerve fiber can be a nerve fiber that has a direct link with a specific nucleus, can be a nerve fiber that passes through a specific region, and can also be a nerve fiber that is related to a specific disease. After determining the target nerve fiber, the doctor can further verify the accuracy and relevance of the target nerve fiber. In application, this can be achieved by comparing with clinical data, pathological reports or other medical knowledge. In actual application, if any inconsistency or further refinement is found, the doctor can adjust the screening target to redetermine the target nerve fiber.

[0127] The corresponding formula can also be generated according to the name of the preset nucleus set by the doctor, the logical relationship corresponding to the positional relationship between the preset nucleus and the target nerve fiber, and then the target nerve fiber is extracted according to the formula. For example, according to the name of the preset nucleus set by the doctor, the logical relationship corresponding to the positional relationship between the preset nucleus and the target nerve fiber, the corresponding formula is generated:!Left-Lenticula|Left-NAc^Left-Lenticula&Left-NAc. The formula indicates that the target nerve fiber includes all nerve fibers that are not linked to the preset nucleus Left-Lenticula, nerve fibers with tails located in the preset nucleus Left-NAc, and nerve fibers with heads located in the preset nucleus Left-Lenticula and linked to the preset nucleus Left-NAc. Referring to FIG. 4, the nerve fiber set related to the left lenticular nucleus is obtained by tracking and screening.

[0128] In the above formula, “Left-Lenticula” and “Left-NAc” represent the names of different preset nuclei; “!Left-Lenticula” represents all nerve fibers that are not linked to the preset nucleus Left-Lenticula, which belongs to a non-set; “|” represents nerve fibers linked to the preset nucleus in front or linked to the preset nucleus behind, which belongs to a union set; “Left-NAc$” represents nerve fibers with tails located in the preset nucleus Left-NAc; “^Left-Lenticula” represents nerve fibers with heads located in the preset nucleus Left-Lenticula; “&” represents nerve fibers linked to the preset nucleus in front and linked to the preset nucleus behind, which belongs to an intersection set.

[0129] In the calculation, the "Left-Lenticula", "Left-NAc$" and "^Left-Lenticula" are calculated first, and then the intersection calculation and the union calculation are performed in sequence, and finally the target nerve fiber is obtained.

[0130] The preset nuclei include target nuclei and / or non-target nuclei; and the target association relationship includes nerve fibers linking at least one target nucleus, or nerve fibers not linking at least one non-target nucleus, or nerve fibers linking at least one target nucleus and not linking at least one non-target nucleus. The classification of the preset nuclei and the target association relationship are further specified, so that the screening process is more accurate.

[0131] The target nerve fiber in the embodiment of the application includes (1) to (3) cases.

[0132] (1) The nerve fiber links one or more preset nuclei but does not link another one or more preset nuclei. The head or tail of the nerve fiber is located inside one or more preset nuclei or the nerve fiber passes through one or more preset nuclei (for example, target nuclei), but the head or tail of the nerve fiber is not located inside another one or more preset nuclei or the nerve fiber does not pass through another one or more preset nuclei (for example, non-target nuclei). Those nerve fibers linking to a specific target nucleus but not directly linking to a specific non-target nucleus can be screened out.

[0133] (2) The nerve fiber links one or more preset nuclei and links another one or more preset nuclei. The head or tail of the nerve fiber is located inside one or more preset nuclei or the nerve fiber passes through one or more preset nuclei (for example, target nuclei), and the head or tail of the nerve fiber is located inside another one or more preset nuclei or the nerve fiber passes through another one or more preset nuclei (for example, target nuclei). Those nerve fibers linking to multiple specific target nuclei at the same time can be screened out, and these nerve fibers may play a bridge role between multiple brain areas or functional regions.

[0134] (3) The nerve fiber does not link one or more preset nuclei but links another one or more preset nuclei. The head or tail of the nerve fiber is not located inside one or more preset nuclei or the nerve fiber does not pass through one or more preset nuclei (for example, target nuclei), and the head or tail of the nerve fiber is located inside another one or more preset nuclei or the nerve fiber passes through another one or more preset nuclei (for example, target nuclei). Those nerve fibers avoiding a specific non-target nucleus but linking to a specific target nucleus can be screened out, which provides a method for studying a specific path of a neural network or avoiding a lesion area.

[0135] Step S4: Obtain display information (such as color identification) for the target nerve fiber.

[0136] In application, identification information for identifying the target nerve fiber is determined. The identification information includes color, label, number or other visual elements, so as to be distinguished from other parts of the target nerve fiber or background when displayed. The identification information of the embodiments of the present application includes color identification, and one or more colors can be selected to distinguish different target nerve fibers or different association relationships. Each color has sufficient contrast, and the path and connection of the nerve fiber can be clearly seen when displayed, so as to clearly distinguish and identify the target nerve fiber in the three-dimensional model or the related visualization interface.

[0137] Step S5: Load the three-dimensional model of the patient's brain into the display screen, and render the target nerve fiber in the three-dimensional model of the patient's brain through the display information, so as to display the target nerve fiber through the display screen.

[0138] The present application displays the screened target nerve fiber in an intuitive way, which is convenient for doctors to observe and analyze, and improves the accuracy and efficiency of diagnosis.

[0139] The three-dimensional model of the patient's brain is loaded, and the identification information is applied to the target nerve fiber using a graphics rendering engine or a special software tool, for example, the path, node or connection point of the nerve fiber is highlighted in a specific color or style. The rendered target nerve fiber is integrated into the three-dimensional model, ensuring that its position and shape in the three-dimensional space are consistent with the original model. The processed three-dimensional model is displayed through the display screen, and the target nerve fiber is displayed with clear identification information. In application, the doctor or can rotate, scale or translate the model through the interactive interface, so as to observe the target nerve fiber from different angles and levels. It can be seen that the present application can display the target nerve fiber in the three-dimensional model on the display screen in an intuitive way, so that the doctor can quickly identify and analyze the position, shape and connection relationship of the target nerve fiber, so as to more accurately diagnose diseases, develop treatment plans or perform surgical simulation.

[0140] The present application is based on medical image data of a patient, and according to a preset nucleus and a correlation between the preset nucleus and a target nerve fiber, a doctor can more accurately identify a target nerve fiber having a specific positional relationship with the preset nucleus, that is, screen a nerve fiber (for example, a target nerve fiber) that plays a role in stimulating a specific nucleus (for example, a preset nucleus), which can improve the accuracy, reliability and analysis efficiency of diagnosis, and provide medical reference materials for the doctor to develop more personalized and precise treatment strategies. For example, the doctor can plan a surgical path in brain surgery according to the fact that when a certain preset nucleus is stimulated, electrical stimulation will be conducted to other brain regions along the target nerve fiber, affecting other parts of the brain, avoiding damage to important neural structures, and improving the safety and effectiveness of the surgery.

[0141] By analyzing the positional relationship between the nerve fiber and the nucleus in different patients or different disease states, the structure and function of the whole brain nerve fiber can be better understood, and the medical level can be greatly improved.

[0142] In addition, the present application not only considers whether the nerve fiber links the nucleus, but also further determines the positional relationship between the target nerve fiber and the preset nucleus, including whether the head or tail of the target nerve fiber is located in the preset nucleus, or whether the target nerve fiber passes through the preset nucleus, so that the doctor can accurately limit the positional relationship between the target nerve fiber and the preset nucleus, thereby reducing the noise in the target nerve fiber, accurately screening the target nerve fiber that meets the conditions, and helping the doctor to avoid misjudgment in the diagnosis process and improve the accuracy of diagnosis.

[0143] The doctor can set different screening conditions to screen the target nerve fiber having a specific positional relationship with a specific nucleus (a preset nucleus) according to the specific condition of the patient, so as to assist the doctor to develop a more personalized and precise treatment plan and improve the treatment effect.

[0144] In the technical field of providing a screening method of a nerve fiber, the present application further introduces a screening device of a nerve fiber.

[0145] Referring to FIG. 3, the screening device of the nerve fiber includes an acquisition module, a correlation module and a target nerve module.

[0146] The acquisition module is configured to acquire medical image data of a patient, and the medical image data includes nerve fiber data and nucleus data. The correlation module is configured to determine the correlation between the nucleus and the nerve fiber according to the acquired nerve fiber data and nucleus data. The target nerve module is configured to determine at least one target nerve fiber according to the screening target of the doctor and the correlation between the nucleus and the nerve fiber.

[0147] The application can automatically and efficiently realize the screening of nerve fibers, reduce the work burden of doctors, and improve the accuracy and efficiency of screening.

[0148] In an embodiment of the present application, the association module comprises a nerve fiber sub-module, a nucleus sub-module, a three-dimensional model sub-module, an extension line sub-module, and an association sub-module.

[0149] The nerve fiber sub-module is configured to cluster the sampling point coordinates with the same identifier to obtain a corresponding sampling point coordinate set of the nerve fiber, and serially process the sampling point coordinates in each sampling point coordinate set to obtain a nerve fiber model corresponding to each sampling point coordinate set in the brain of the patient. The nucleus sub-module is configured to generate a nucleus model of the brain of the patient according to the model data of each nucleus in the brain of the patient. The three-dimensional model sub-module is configured to place each nerve fiber model and each nucleus model in a three-dimensional simulation environment of the brain of the patient to determine a three-dimensional model of the brain of the patient. The extension line sub-module is configured to extend from any point on any nerve fiber in the nerve fiber model in the three-dimensional model in any direction to obtain an extension line. The association sub-module is configured to determine the association relationship between the nerve fiber and the nucleus according to the intersection relationship between the extension line and the nucleus in the nucleus model in the three-dimensional model. For example, the nerve fiber links the nucleus or the nerve fiber does not link the nucleus.

[0150] In another embodiment of the present application, the target nerve module comprises a preset nucleus sub-module, a preset relationship sub-module, a target sub-module, and a visualization sub-module.

[0151] The preset nucleus sub-module comprises a plurality of preset nucleus units configured to set the preset nucleus. In application, some preset nucleus units are configured to set the lenticular nucleus, some preset nucleus units are configured to set the caudate nucleus, and some preset nucleus units are configured to set the septal nucleus.

[0152] The preset relationship sub-module comprises a plurality of preset position units configured to set the position relationship between the preset nucleus and the target nerve fiber. In application, some preset position units are configured to set the specific position of the target nerve fiber and the preset nucleus, some preset position units are configured to set the union, some preset position units are configured to set the non-union, and some preset position units are configured to set the intersection.

[0153] The target sub-module is configured to form the target nerve fiber according to the signals of the plurality of preset nucleus units, the plurality of preset position units, and the position module.

[0154] The visualization sub-module is configured to display the target nerve fiber formed by the target sub-module. In application, the visualization sub-module can also display the change of the target nerve fiber in the process of screening and obtaining the target nerve fiber.

[0155] The preset nucleus group sub-module and the preset relationship sub-module are arranged, so that the doctor can flexibly set the position relationship between the preset nucleus group and the target nerve fiber according to the needs of a specific case, the screening process is simple and convenient to operate, and the pertinence and screening effect are improved.

[0156] The preset nucleus group unit and the preset position unit are arranged, so that the operation process is more simple and intuitive, the doctor only needs to select the preset nucleus group and the position relationship between the preset nucleus group and the target nerve fiber on the interface, and the target sub-module can automatically complete the screening process, which greatly simplifies the operation steps, reduces the operation difficulty and error rate of the doctor, and improves the work efficiency.

[0157] The visual sub-module is arranged, and in the process of screening and obtaining the target nerve fiber, the position relationship between the target nerve fiber and the preset nucleus group is displayed in a visual manner, so that the doctor can more intuitively understand and analyze the data, which helps the doctor better grasp the disease condition and improves the pertinence and effect of treatment.

[0158] In the technical field of providing a nerve fiber screening method, the application further introduces a medical device.

[0159] The medical device of the application includes a processor, a memory, and a computer program stored on the memory, and the processor executes the computer program to implement the above-mentioned nerve fiber screening method.

[0160] The application integrates the nerve fiber screening method into the medical device, so that the method can be conveniently applied to the actual medical environment, and the level and efficiency of medical services are improved.

[0161] In the technical field of providing a nerve fiber screening method, the application further introduces a computer readable storage medium.

[0162] The computer readable storage medium of the application stores a computer program / instruction, and the computer program / instruction is implemented by a processor to implement the above-mentioned nerve fiber screening method. The storage medium can be a non-transitory storage medium.

[0163] The application integrates the nerve fiber screening method into the computer readable storage medium, so that the method can be conveniently stored.

[0164] In the technical field of providing a nerve fiber screening method, the application further introduces a computer program product.

[0165] The computer program product of the application includes a computer program / instruction, and the computer program / instruction is implemented by a processor to implement the above-mentioned nerve fiber screening method.

[0166] The present application provides a product containing computer programs or instructions implementing the screening method, facilitating use on different devices.

[0167] Although the embodiments of the present application have been shown and described above, it should be understood by those skilled in the art that the above embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above embodiments without departing from the principles and purposes of the present application within the scope of the application, and all these changes should belong to the protection scope of the claims of the present application.

Claims

1. A method for screening nerve fibers, comprising: Acquire the patient's medical imaging data, wherein the medical imaging data includes nerve fiber data and nucleus data; Based on the nerve fiber data and the nucleus data, the relationship between the nucleus and the nerve fiber is determined; Based on the screening targets and the relationship between the nuclei and nerve fibers, at least one target nerve fiber is identified.

2. The method according to claim 1, wherein, The relationships between the nuclei and nerve fibers include: The positional relationship between any nucleus and any nerve fiber, wherein the positional relationship includes nerve fibers linking to or not linking to nuclei.

3. The method according to claim 1, wherein, The step of determining the relationship between nuclei and nerve fibers based on the nerve fiber data and the nucleus data includes: Based on the nerve fiber data and the nucleus data, a nerve fiber model and a nucleus model of the patient's brain were determined respectively. The association between the nuclei and nerve fibers was determined based on the positional relationship between each nerve fiber model and each nucleus model in the patient's brain.

4. The method according to claim 3, wherein, The process of determining the association between the nuclei and nerve fibers based on the positional relationship of each nerve fiber model and each nucleus model in the patient's brain includes: Each nerve fiber model and each nucleus model was placed in a three-dimensional simulation environment of the patient's brain to determine the three-dimensional model of the patient's brain; Based on the three-dimensional model of the patient's brain, the spatial location of each nerve fiber model and each nucleus model in the patient's brain is determined, and the relationship between the nuclei and nerve fibers is determined based on the spatial location.

5. The method according to claim 3, wherein, The process of determining the association between the nuclei and nerve fibers based on the positional relationship of each nerve fiber model and each nucleus model in the patient's brain includes: Each nerve fiber model and each nucleus model was placed in a three-dimensional simulation environment of the patient's brain to determine the three-dimensional model of the patient's brain; An extension line is obtained by extending any point on any nerve fiber in the nerve fiber model of the three-dimensional model in any direction. The relationship between the nuclei and nerve fibers is determined based on the intersection of the extension line with the nuclei in the nucleus model of the three-dimensional model.

6. The method according to claim 5, wherein, The step of determining the association between the nucleus and nerve fiber based on the intersection relationship between the extension line and the nucleus in the nucleus model of the three-dimensional model includes at least one of the following: In response to the extension line intersecting with at least one nucleus, and having only one intersection point with the at least one nucleus, it indicates that the nerve fiber is connected to at least one nucleus; or, In response to the extension line intersecting at least one nucleus and having two intersection points with the at least one nucleus, the nerve fiber does not connect to the at least one nucleus.

7. The method according to claim 3, wherein, The nerve fiber data includes the sampling point coordinates of the nerve fibers, and the sampling point coordinates include the identifier of the nerve fibers, each nerve fiber having a different identifier. The nucleus data includes model data of each nucleus in the patient's brain. The process of determining the neural fiber model and the nucleus model of the patient's brain based on the neural fiber data and the nucleus data, respectively, includes: Clustering of sampling point coordinates with the same identifier yields the set of sampling point coordinates for the corresponding nerve fiber. By concatenating the coordinates of the sampling points in each set of sampling points, a neural fiber model corresponding to each set of sampling point coordinates in the patient's brain is obtained. A model of the brain nuclei of the patient is generated based on model data of each nucleus in the patient's brain.

8. The method according to claim 2, wherein, The nerve fiber connection nuclei include: The ends of nerve fibers are located inside the nucleus, or the nerve fibers pass through the nucleus.

9. The method according to claim 1, wherein, The screening targets include at least one preset nucleus and nerve fibers that are associated with the at least one preset nucleus.

10. The method according to claim 9, wherein, The preset nucleus includes at least one of the following: a target nucleus or a non-target nucleus; The target association relationships include: Nerve fibers linking to at least one target nucleus, or Neural fibers that do not link to at least one non-target nucleus, or It links to at least one target nucleus and does not link to at least one non-target nucleus nerve fiber.

11. The method according to claim 1, wherein, The method further includes: Obtain display information for the at least one target nerve fiber; A three-dimensional model of the patient's brain is loaded onto a display screen, and the target nerve fibers in the three-dimensional model of the patient's brain are rendered using the display information, so as to display the target nerve fibers on the display screen.

12. A nerve fiber screening device, comprising: The acquisition module is configured to acquire the patient's medical imaging data, wherein the medical imaging data includes nerve fiber data and nucleus data; The association module is configured to determine the association relationship between the nuclei and the nerve fibers based on the nerve fiber data and the nucleus data; The target neural module is configured to identify at least one target nerve fiber based on the screening target and the association between the nuclei and nerve fibers.

13. A medical device comprising a processor, a memory, and a computer program stored in the memory, wherein, The processor executes the computer program to implement the method for screening nerve fibers according to any one of claims 1 to 11.

14. A computer-readable storage medium having a computer program / instructions stored thereon, wherein, The computer program / instructions are implemented by a processor using the method for screening nerve fibers according to any one of claims 1 to 11.

15. A computer program product comprising a computer program / instructions, wherein, When the computer program / instructions are executed by the processor, they implement the method for screening nerve fibers according to any one of claims 1 to 11.

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