DTI-ALPS mapping graph generation method and system, electronic equipment and storage medium

Abstract

The invention discloses a DT I-ALPS mapping graph generation method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining a medical image, carrying out the fiber mapping calculation of the medical image, and obtaining a fiber diffusivity value; performing region-of-interest positioning processing on the medical image to obtain a reference region-of-interest; according to the fiber diffusivity value and the reference region of interest, performing three-dimensional voxel-by-voxel calculation processing on nerve fibers in the medical image to obtain DT I-ALPS indexes of different spatial resolutions; and performing pseudo-color display processing on the medical image according to the DT I-ALPS index to obtain a mapping graph. According to the embodiment of the invention, the DT I-ALPS index can be displayed more visually, and the method can be widely applied to the technical field of image processing.

Description

Technical Field

[0001] The present application relates to the field of image processing technology, and in particular to a method, system, electronic device and storage medium for generating a DTI-ALPS map. Background Art

[0002] In the related art, there is a method for calculating the DTI-ALPS index by manually selecting a region of interest (ROI). This involves manually selecting an ROI and performing calculations within it. However, in actual applications, it has been found that due to inconsistent ROI selection criteria, the calculation results are easily affected by the deviation of the manually selected area. Furthermore, the ROI methods used in related art often only analyze local areas and cannot fully reflect the overall picture of glymphatic system activity in the brain. This leads to certain deficiencies in the accuracy and comprehensiveness of related technologies, affecting the efficiency of DTI-ALPS map generation.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main purpose of the embodiments of the present application is to propose a method, system, electronic device and storage medium for generating a DTI-ALPS map, which can improve the efficiency of map generation.

[0005] To achieve the above objectives, an embodiment of the present application provides a method for generating a DTI-ALPS map, the method comprising:

[0006] Acquiring a medical image, performing fiber mapping calculation processing on the medical image, and obtaining a fiber diffusivity value;

[0007] performing region of interest positioning processing on the medical image to obtain a reference region of interest;

[0008] Performing three-dimensional voxel-by-voxel computation on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions;

[0009] The medical image is subjected to pseudo-color display processing according to the DTI-ALPS index to obtain a mapping image.

[0010] In some embodiments, performing fiber mapping calculation processing on the medical image to obtain a fiber diffusivity value comprises the following steps:

[0011] performing preprocessing and registration processing on the medical image to obtain a diffusion component map;

[0012] performing positioning processing on the medical image based on a fiber bundle template to obtain a fiber map;

[0013] The diffusion component map and the fiber map are multiplied to obtain the fiber diffusivity value.

[0014] In some embodiments, performing three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions includes the following steps:

[0015] Positioning the nerve fibers according to a preset voxel step size to obtain a target region of interest;

[0016] Performing index calculation processing on the target region of interest and the reference region of interest according to the fiber diffusivity value to obtain a DTI-ALPS index corresponding to the preset voxel step size;

[0017] The preset voxel step size is adjusted, and the process returns to the process of positioning the nerve fibers according to the preset voxel step size, until the adjustment of the preset voxel step size is completed, thereby obtaining DTI-ALPS indices with different spatial resolutions.

[0018] In some embodiments, performing index calculation processing on the target region of interest and the reference region of interest according to the fiber diffusivity value to obtain a DTI-ALPS index corresponding to the preset voxel step size includes the following steps:

[0019] Determine the projection fiber region of interest and the contact fiber region of interest according to the reference region of interest;

[0020] determining projection fiber voxels and contact fiber voxels according to the target region of interest;

[0021] performing index calculation processing on the connection fiber voxel according to the fiber diffusivity value and the projected fiber region of interest to obtain a connection fiber voxel index value;

[0022] performing index calculation processing on the projected fiber voxel according to the fiber diffusivity value and the connection fiber region of interest to obtain a projected fiber voxel index value;

[0023] The DTI-ALPS index is obtained according to the connection fiber voxel index value and the projection fiber voxel index value.

[0024] In some embodiments, performing index calculation processing on the connection fiber voxel according to the fiber diffusivity value and the projected fiber region of interest to obtain the connection fiber voxel index value comprises the following steps:

[0025] Calculating and processing the connection fiber voxel according to the fiber diffusivity value to obtain a first direction diffusivity value and a second direction diffusivity value;

[0026] Calculating and processing the projected fiber region of interest according to the fiber diffusivity value to obtain a first diffusivity value and a second diffusivity value;

[0027] performing an average calculation process on the first-directional diffusivity value and the first diffusivity value to obtain a first average value;

[0028] performing an average calculation process on the second-direction diffusivity value and the second diffusivity value to obtain a second average value;

[0029] A ratio calculation process is performed on the first average value and the second average value to obtain the connection fiber voxel index value.

[0030] In some embodiments, performing index calculation processing on the projected fiber voxel according to the fiber diffusivity value and the contact fiber region of interest to obtain a projected fiber voxel index value comprises the following steps:

[0031] Calculating and processing the connection fiber voxel according to the fiber diffusivity value to obtain a third direction diffusivity value and a fourth direction diffusivity value;

[0032] Calculating and processing the projected fiber region of interest according to the fiber diffusivity value to obtain a third diffusivity value and a fourth diffusivity value;

[0033] performing an average calculation process on the third-direction diffusivity value and the third diffusivity value to obtain a third average value;

[0034] performing average calculation processing on the fourth-direction diffusivity value and the fourth diffusivity value to obtain a fourth average value;

[0035] A ratio calculation process is performed on the third average value and the fourth average value to obtain the projected fiber voxel index value.

[0036] In some embodiments, performing pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image includes the following steps:

[0037] Performing format conversion processing on the medical image according to the DTI-ALPS index to obtain a standard format image;

[0038] Performing color image conversion processing on the standard format image to obtain the mapping image.

[0039] To achieve the above objectives, another aspect of the present invention provides a system for generating a DTI-ALPS map, the system comprising:

[0040] The first module is used to acquire a medical image, perform fiber mapping calculation processing on the medical image, and obtain a fiber diffusivity value;

[0041] The second module is used to perform region of interest positioning processing on the medical image to obtain a reference region of interest;

[0042] A third module is configured to perform three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions;

[0043] The fourth module is used to perform pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image.

[0044] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application provides an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned method when executing the computer program.

[0045] To achieve the above objectives, another aspect of an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0046] The embodiments of the present application include at least the following beneficial effects: The present application provides a method, system, electronic device, and storage medium for generating a DTI-ALPS map. This solution acquires a medical image, performs fiber mapping calculations on the medical image, and obtains fiber diffusivity values, which can provide a computational basis for subsequent index calculations. Furthermore, this solution performs region-of-interest (ROI) location processing on the medical image to obtain a reference ROI; based on the fiber diffusivity values and the reference ROI, three-dimensional voxel-by-voxel calculations are performed on the nerve fibers in the medical image to obtain DTI-ALPS indices of varying spatial resolutions. This solution can perform coverage calculations on the nerve fibers in the medical image based on the diffusivity data, and can generate DTI-ALPS maps of varying spatial resolutions. Furthermore, this solution performs pseudo-color display processing on the medical image based on the DTI-ALPS index to obtain a map that can more intuitively display the DTI-ALPS index. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flowchart of a method for generating a DTI-ALPS map provided in an embodiment of the present application;

[0048] Figure 2 yes Figure 1 Flowchart of step S101 in FIG.

[0049] Figure 3 is a schematic diagram of a fiber bundle template provided in an embodiment of the present application;

[0050] Figure 4 yes Figure 1 Flowchart of step S103 in FIG.

[0051] Figure 5 yes Figure 4 Flowchart of step S402 in FIG.

[0052] Figure 6 yes Figure 5 Flowchart of step S503 in FIG.

[0053] Figure 7 yes Figure 5 Flowchart of step S504 in FIG.

[0054] Figure 8 1 is a schematic structural diagram of a DTI-ALPS map generation system provided in an embodiment of the present application;

[0055] Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. They are merely examples of systems and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0057] It will be understood that the terms "first", "second", etc. used in this application may be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0058] The terms "at least one", "plurality", "each", "any", etc. used in this application include "at least one", "two" or more, "plurality" or "each", "any" or "any one", "each" or "any one" as used herein.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0060] Before explaining the embodiments of the present application in detail, some of the nouns and terms involved in the embodiments of the present application are first explained. The nouns and terms involved in the embodiments of the present application are subject to the following explanations.

[0061] 1) Diffusion Tensor Imaging Analysis of Perivascular Spaces (DTI-ALPS) is a noninvasive imaging technique for assessing the function of the cerebral glymphatic system. It uses diffusion tensor imaging to analyze the diffusion of water molecules in the perivascular space. It can be used to noninvasively measure the activity of the cerebral glymphatic system, avoiding the need for contrast agent injection.

[0062] 2) Region of Interest (ROI) refers to the area of interest that needs to be processed, which is outlined in the image using a box, circle, ellipse, or irregular polygon. Various operators and functions can be used to determine the ROI and then perform further image processing. This method is widely used in areas such as heat map, face recognition, and image segmentation.

[0063] 3) A voxel is the smallest unit of volume in three-dimensional space, similar to a two-dimensional pixel. Voxels are used as the basic unit of data in three-dimensional imaging applications such as CT and MRI.

[0064] In the related art, the relevant DTI-ALPS method mainly relies on manual selection of regions of interest (ROI), and the selection criteria of ROI are not yet unified. The limitation of this approach is that its calculation results are easily affected by the deviation of manually selected regions. At the same time, the relevant ROI methods often only analyze local areas and cannot fully reflect the overall picture of glymphatic system activity in the brain. Therefore, the accuracy and comprehensiveness of the existing methods have certain shortcomings. Studies have shown that although the geometric shape of the ROI has little effect on the calculation of the ALPS index, the size and selection criteria of the ROI have a significant impact on the accuracy of the final result.

[0065] For example, relevant DTI-ALPS studies generally adopt ROI-based calculation methods, which manually select ROIs and perform calculations within their range. Common ROI selection methods can be roughly divided into three categories: (1) ROIs with the same geometric shape and fixed y-axis and z-axis coordinates; (2) ROIs with the same geometric shape but different coordinate positions; (3) ROI studies based on specific fiber bundle regions. Because these methods rely on the selection of local regions, it is difficult to fully reflect the activity distribution of the glymphatic system in the whole brain. In addition, ROI selection may introduce human bias, further affecting the accuracy of the calculation results. At present, no study has proposed a method that can calculate the DTI-ALPS index and generate a map across the whole brain, thereby intuitively showing the activity distribution of the glymphatic system in different white matter structures.

[0066] The brain possesses a lymphatic system similar to that in the periphery of the body, known as the glymphatic system, which is responsible for transporting and clearing waste products from the brain. However, a noninvasive method to comprehensively assess the activity of the brain's glymphatic system is currently lacking. In recent years, studies have preliminarily validated the potential of diffusion tensor magnetic resonance imaging (DTI)-alongside-the-vascular-space index (DTI-ALPS) in reflecting glymphatic system function. However, the related DTI-ALPS method has significant technical limitations: first, it relies on manual selection of regions of interest (ROIs), a process that is not only highly subjective and leads to uncertainty in the calculation results, but also makes it difficult to capture spatial differences between different brain regions; second, it uses a single numerical value to represent global glymphatic system activity, which cannot demonstrate the spatial distribution characteristics of the entire brain. Therefore, these methods cannot meet the needs for accurate quantification and comprehensive visualization of glymphatic system activity.

[0067] In view of this, the embodiments of the present application provide a method, system, electronic device and storage medium for generating a DTI-ALPS mapping diagram. The solution obtains a medical image, performs fiber mapping calculation processing on the medical image, and obtains a fiber diffusion rate value, which can provide a calculation basis for subsequent index calculation. In addition, the solution obtains a reference region of interest by performing region of interest positioning processing on the medical image; performs three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image based on the fiber diffusion rate value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions, and can perform coverage calculation on the nerve fibers in the medical image based on the diffusion rate data, and can generate DTI-ALPS mapping diagrams of different spatial resolutions. Moreover, the solution performs pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping diagram, which can more intuitively display the DTI-ALPS index and clearly show the activity differences between different brain regions.

[0068] The embodiment of the present application provides a method for generating a DTI-ALPS mapping diagram, which relates to the field of image processing technology. The embodiment of the present application provides a method for generating a DTI-ALPS mapping diagram that can be applied to a terminal, a server, or software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and a car terminal, etc., but is not limited to this; the server side can be configured as an independent physical server, or as a server cluster or distributed system consisting of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network; the software can be an application that implements a method for generating a DTI-ALPS mapping diagram, etc., but is not limited to the above forms.

[0069] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.

[0070] Figure 1 This is an optional flowchart of a method for generating a DTI-ALPS map provided in an embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S104.

[0071] Step S101, acquiring a medical image, performing fiber mapping calculation processing on the medical image, and obtaining a fiber diffusivity value;

[0072] Step S102, performing region of interest positioning processing on the medical image to obtain a reference region of interest;

[0073] Step S103, performing three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions;

[0074] Step S104 : performing pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image.

[0075] In the steps S101 to S104 shown in the embodiment of the present application, by performing fiber mapping calculation processing on the medical image, the diffusion rate values of the bilateral projection fibers and the joint fibers in the medical image can be calculated, which can provide a data basis for the subsequent DTI-ALPS index calculation. Then, the embodiment of the present application obtains a reference region of interest by performing region of interest positioning processing on the medical image. The reference region of interest is a fixed region of interest, which is used to calculate the diffusion rate value of any area within the range of the projection fibers and the connection fibers. The embodiment of the present application performs three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image based on the fiber diffusion rate value and the reference region of interest. By treating the voxels on the nerve fibers as an independent target region of interest, the voxel-level DTI-ALPS can be calculated along the projection fibers and the connection fibers. And by adjusting the step size when traversing the voxels, DTI-ALPS mapping diagrams of different spatial resolutions are generated. Finally, the medical image is pseudo-colored according to the DTI-ALPS index to obtain a mapping diagram, which can more intuitively display the distribution of lymphatic system activity.

[0076] One of the above technical solutions has the following advantages or beneficial effects: By calculating DTI-ALPS values on nerve fibers voxel by voxel, this embodiment of the application can cover the projection fibers and associated fibers of the white matter region voxel by voxel based on diffusivity data, thereby achieving an intuitive and comprehensive assessment of glymphatic system activity. Furthermore, by adjusting the step size when traversing voxels, this embodiment of the application generates DTI-ALPS maps of varying spatial resolutions, enabling adjustable resolution to meet diverse analytical needs.

[0077] See also Figure 2 In step S101 of some embodiments, performing fiber mapping calculation processing on the medical image to obtain a fiber diffusivity value includes the following steps:

[0078] Step S201, performing preprocessing and registration processing on the medical image to obtain a diffusion component map;

[0079] Step S202, performing positioning processing on the medical image based on the fiber bundle template to obtain a fiber map;

[0080] Step S203: multiply the diffusion component map and the fiber map to obtain the fiber diffusivity value.

[0081] In the embodiment of the present application, the medical image is an image containing nerve fiber images, which can be obtained through diffusion tensor magnetic resonance imaging or obtained from a public database, and there is no limitation here.

[0082] In embodiments of the present application, medical images can be preprocessed and registered to generate diffusion component maps in the x, y, and z directions of three-dimensional space. The preprocessing process includes format conversion and standardization, denoising and artifact removal, eddy current and head motion correction, and field distortion correction. Registration includes brain region segmentation and spatial registration. Finally, a diffusion component map is generated using a multimodal medical image processing platform using tensor model fitting and directional component visualization.

[0083] See also Figure 3 , the fiber bundle template can adopt the JHU-ICBM DTI-81Atlas template, which is based on the brain white matter fiber bundle template of diffusion tensor imaging (DTI) for locating and analyzing the main fiber bundles of the brain. It is conceivable that the embodiment of the present application can also adopt other open source fiber bundle templates. Through this template, the areas of projection fibers and connection fibers can be selected respectively in the left and right brain images in the medical image. The template divides the projection fibers and connection fibers into 30 areas. Finally, by multiplying the fiber map obtained by drawing with the diffusion component map, the diffusivity values of the bilateral projection fibers and the joint fibers in the x, y and z directions are extracted therefrom to obtain the fiber diffusivity values, thereby providing necessary preparations for the subsequent DTI-ALPS index calculation.

[0084] One of the above technical solutions has the following advantages or beneficial effects: the embodiment of the present application can improve the accuracy of the data and remove the corresponding noise by preprocessing and aligning the medical images, and obtain the fiber diffusion rate value by calculation, which can provide a data basis for the subsequent calculation of the DTI-ALPS index.

[0085] In step S102 of some embodiments, the medical image is subjected to region of interest positioning processing to obtain a reference region of interest.

[0086] In the embodiment of the present application, the reference region of interest can be located according to the set coordinates and can be modified according to actual conditions. The modification standard is that the reference region of interest is as close as possible to the projection fiber and the communication fiber. In a feasible embodiment, the reference region of interest includes four fixed regions of interest with coordinate centers of (24, -12, 24), (-28, -12, 24), (36, -12, 24) and (-40, -12, 24), corresponding to the right projection fiber and the left projection fiber as well as the right communication fiber and the left communication fiber. Each reference region of interest is spherical with a diameter of 6 mm.

[0087] See also Figure 4 In step S103 of some embodiments, performing three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions includes the following steps:

[0088] Step S401, positioning the nerve fibers according to a preset voxel step size to obtain a target region of interest;

[0089] Step S402, performing index calculation processing on the target region of interest and the reference region of interest according to the fiber diffusivity value to obtain a DTI-ALPS index corresponding to the preset voxel step size;

[0090] Step S403 , adjusting the preset voxel step size, returning to the process of positioning the nerve fibers according to the preset voxel step size, until the adjustment of the preset voxel step size is completed, and obtaining DTI-ALPS indices of different spatial resolutions.

[0091] In an embodiment of the present application, the nerve fibers are positioned according to a preset voxel step size, and the voxel step size area on the nerve fibers is used as an independent target region of interest, wherein the voxel step size can be a single voxel, two voxels, and three voxels, etc. Then, the target region of interest and the reference region of interest are indexed and processed according to the fiber diffusivity value. By calculating the DTI-ALPS value voxel by voxel, each voxel can be regarded as an independent movable region of interest, and the projection fibers and joint fibers covering the entire protein area based on the diffusivity data are obtained, thereby obtaining the DTI-ALPS index corresponding to the preset voxel step size. In a feasible embodiment, the voxel step size is first set to a single voxel, and the corresponding DTI-ALPS index is calculated by calculating the corresponding DTI-ALPS index for the projection fibers and joint fibers in the entire medical image. And by adjusting the preset voxel step size, the voxel step size is set to two voxels, that is, the two-voxel space size is used as the target region of interest, and the corresponding DTI-ALPS index is calculated for the projection fibers and joint fibers two voxels at a time. In the embodiment of the present application, the step size when traversing voxels can be adjusted, for example, one voxel at a time, two voxels at a time, or three voxels at a time, to obtain DTI-ALPS indices with different spatial resolutions.

[0092] One of the above technical solutions has the following advantages or beneficial effects: By treating each voxel as a target region of interest, this embodiment of the application provides an intuitive and comprehensive assessment of glymphatic system activity based on diffusivity data covering the projection fibers and associated fibers of the entire protein region. Furthermore, DTI-ALPS maps of varying spatial resolutions can be generated by adjusting the step size when traversing the voxels, enabling flexible resolution selection to meet diverse analysis requirements.

[0093] See also Figure 5 In step S402 of some embodiments, performing index calculation processing on the target region of interest and the reference region of interest based on the fiber diffusivity value to obtain a DTI-ALPS index corresponding to the preset voxel step size includes the following steps:

[0094] Step S501, determining a projection fiber region of interest and a contact fiber region of interest according to the reference region of interest;

[0095] Step S502, determining the projection fiber voxel and the contact fiber voxel according to the target region of interest;

[0096] Step S503, performing index calculation processing on the connection fiber voxel according to the fiber diffusivity value and the projected fiber region of interest to obtain a connection fiber voxel index value;

[0097] Step S504, performing index calculation processing on the projected fiber voxel according to the fiber diffusivity value and the contact fiber region of interest to obtain a projected fiber voxel index value;

[0098] Step S505 : Obtain the DTI-ALPS index according to the contact fiber voxel index value and the projected fiber voxel index value.

[0099] In an embodiment of the present application, in order to achieve voxel-by-voxel calculation, the DTI-ALPS index calculation method is decomposed into two parts to calculate voxel-level DTI-ALPS along the projection fibers and the communication fibers. In the embodiment of the present application, the calculation is performed on the left and right projection and communication fibers respectively to ensure that the same procedure is evenly applied to the two cerebral hemispheres. Among them, the reference region of interest includes the projection fiber region of interest and the communication fiber region of interest. Similarly, the target region of interest includes projection fiber voxels and communication fiber voxels, that is, the corresponding voxel space on the projection fibers and the communication fibers is used as the region of interest for calculation according to the preset voxel step size. By traversing the region of interest step by step, the DTI-ALPS index on all projection fibers and communication fibers in the medical image can be calculated.

[0100] Specifically, the calculation method is divided into two types: calculating the DTI-ALPS index at the voxel level along the projection fibers and calculating the DTI-ALPS index at the voxel level along the connection fibers. The connection fiber voxel index value can be obtained by calculating the index of the connection fiber voxel based on the fiber diffusivity value and the projection fiber region of interest. The projected fiber voxel index value can be obtained by calculating the index of the projection fiber voxel based on the fiber diffusivity value and the connection fiber region of interest. Finally, the calculated connection fiber voxel index value and projection fiber voxel index value are used as the DTI-ALPS index of the medical image.

[0101] One of the above technical solutions has the following advantages or beneficial effects: the embodiment of the present application regards each voxel as a target region of interest, traverses and calculates the DTI-ALPS index on the nerve fiber, and can provide an intuitive and comprehensive evaluation of the lymphatic system activity.

[0102] See also Figure 6 In step S503 of some embodiments, the index calculation processing of the connection fiber voxel according to the fiber diffusivity value and the projected fiber region of interest to obtain the connection fiber voxel index value includes the following steps:

[0103] Step S601, calculating and processing the connection fiber voxel according to the fiber diffusivity value to obtain a first direction diffusivity value and a second direction diffusivity value;

[0104] Step S602, calculating and processing the projected fiber region of interest according to the fiber diffusivity value to obtain a first diffusivity value and a second diffusivity value;

[0105] Step S603, performing average calculation processing on the first directional diffusivity value and the first diffusivity value to obtain a first average value;

[0106] Step S604, performing an average calculation process on the second-directional diffusivity value and the second diffusivity value to obtain a second average value;

[0107] Step S605 , performing ratio calculation processing on the first average value and the second average value to obtain the connection fiber voxel index value.

[0108] In an embodiment of the present application, the connection fiber voxel can be calculated and processed based on the calculated fiber diffusivity value, wherein the fiber diffusivity value is the diffusivity value of each voxel on the projection fiber and the joint fiber in the medical image obtained by performing fiber mapping calculation on the medical image. The connection fiber voxel is the voxel space determined according to the voxel step size on the connection fiber, which is used as the target region of interest for calculation. When the voxel step size is set to a single voxel, the diffusivity value of the voxel can be directly calculated. When the voxel step size is set to multiple voxels, such as two voxels, three voxels, etc., the diffusivity value can be calculated by the average of all voxels covered by the voxel space, so that the diffusivity value of the target region of interest in the x-axis and y-axis directions can be obtained, that is, the first direction diffusivity value and the second direction diffusivity value are obtained. Here, the first direction diffusivity value is the diffusivity value of the voxel space on the connection fiber in the x-axis direction, and the second direction diffusivity value is the diffusivity value of the voxel space on the connection fiber in the y-axis direction.

[0109] The projected fiber ROI is then calculated based on the fiber diffusivity values to obtain a first diffusivity value and a second diffusivity value. The first diffusivity value is the diffusivity value of a fixed ROI within the projected fiber ROI. The first diffusivity value is obtained by averaging the diffusion values of all voxels within a sphere with a corresponding diameter centered at the coordinate. Similarly, the second diffusivity value is the diffusivity value of another ROI.

[0110] The calculated first-direction diffusivity value and the first diffusivity value are averaged to obtain a first average value, and the second-direction diffusivity value and the second diffusivity value are averaged to obtain a second average value. The first average value and the second average value are ratioed to obtain a connection fiber voxel index value. The calculation formula of the connection fiber voxel index value is as follows:

[0111]

[0112] Where ALPSindex_assoc[j] represents the DTI-ALPS index value of the contact fiber voxel, j represents the voxel space on the contact fiber, mean represents the average value calculation, D xx_assoc[j] Indicates the diffusion rate value in the first direction, D xx_proj_fixed represents the first diffusivity value, D zz_assoc[j] Indicates the diffusion rate value in the second direction, D yy_proj_fixed represents the second diffusivity value.

[0113] See also Figure 7 In step S504 of some embodiments, the index calculation processing of the projected fiber voxel according to the fiber diffusivity value and the contact fiber region of interest to obtain the projected fiber voxel index value includes the following steps:

[0114] Step S701, calculating and processing the connection fiber voxel according to the fiber diffusivity value to obtain a third direction diffusivity value and a fourth direction diffusivity value;

[0115] Step S702, calculating and processing the projected fiber region of interest according to the fiber diffusivity value to obtain a third diffusivity value and a fourth diffusivity value;

[0116] Step S703, performing average calculation processing on the third-direction diffusivity value and the third diffusivity value to obtain a third average value;

[0117] Step S704, performing average calculation processing on the fourth-direction diffusivity value and the fourth diffusivity value to obtain a fourth average value;

[0118] Step S705 , performing ratio calculation processing on the third average value and the fourth average value to obtain the projected fiber voxel index value.

[0119] In an embodiment of the present application, the projected fiber voxels can be calculated and processed based on the calculated fiber diffusivity values, wherein the projected diffusivity values are the diffusivity values of each voxel on the projected fibers and the associated fibers in the medical image obtained by performing fiber mapping calculations on the medical image. The projected fiber voxels are voxel spaces determined based on the voxel step size on the projected fibers, and are used as the target region of interest for calculation. When the voxel step size is set to a single voxel, the diffusivity value of the voxel can be directly calculated. When the voxel step size is set to multiple voxels, such as two voxels or three voxels, the diffusivity value can be calculated based on the average of all voxels covered by the voxel space, thereby obtaining the diffusivity values of the target region of interest in the x-axis and y-axis directions, that is, obtaining the third direction diffusivity value and the fourth direction diffusivity value. Here, the third direction diffusivity value is the diffusivity value of the voxel space on the projected fibers in the x-axis direction, and the fourth direction diffusivity value is the diffusivity value of the voxel space on the projected fibers in the y-axis direction.

[0120] The connecting fiber ROI is then calculated based on the fiber diffusivity values to obtain a third diffusivity value and a fourth diffusivity value. The third diffusivity value is the diffusivity value of a fixed ROI within the connecting fiber ROI. The first diffusivity value is obtained by averaging the diffusion values of all voxels within a sphere with a corresponding diameter centered at the coordinate. Similarly, the fourth diffusivity value is the diffusivity value of another ROI.

[0121] The calculated third-direction diffusivity value and the third diffusivity value are averaged to obtain a third average value, and the fourth-direction diffusivity value and the fourth diffusivity value are averaged to obtain a fourth average value. The third average value and the fourth average value are ratioed to obtain a projected fiber voxel index value. The calculation formula of the projected fiber voxel index value is as follows:

[0122]

[0123] Where ALPSindex_proj[i] represents the DTI-ALPS index value of the projected fiber voxel, i represents the voxel space on the projected fiber, mean represents the average value calculation, and D xx_proj[i] Indicates the diffusion rate value in the third direction, D xx_assoc_fixed represents the third diffusivity value, D yy_proj[i] Indicates the diffusion rate value in the fourth direction, D zz_assoc_fixed represents the fourth diffusivity value.

[0124] In step S104 of some embodiments, performing pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image includes the following steps:

[0125] Performing format conversion processing on the medical image according to the DTI-ALPS index to obtain a standard format image;

[0126] Performing color image conversion processing on the standard format image to obtain the mapping image.

[0127] In embodiments of the present application, the calculated DTI-ALPS index can be used to convert the medical image format to a standard format, such as the NII file format, thereby obtaining a standard format image. The NII file format stores the physical location of voxels occupying a certain volume in space and the corresponding pixel values. Image viewing software can directly assign pseudo colors to standard format images, thereby converting them into color maps for easy viewing.

[0128] The following is a detailed description of the embodiments of the present application with reference to specific application examples:

[0129] The embodiments of the present application can be applied to the technical field of medical image processing, and are suitable for data analysis application scenarios such as evaluating the activity of the brain's glymphatic system. In a usable embodiment, the embodiment of the present application can generate a DTI-ALPS map over the entire brain by calculating DTI-ALPS voxel by voxel. This method does not require manual selection of ROIs, significantly reduces the risk of selection bias, and comprehensively displays the distribution characteristics of the brain's glymphatic system activity in different white matter structures, thereby more accurately and comprehensively reflecting the activity of the entire brain. Automated analysis can be achieved with a standardized process, significantly improving the accuracy and repeatability of the results.

[0130] Specifically, the embodiment of the present application generates the DTI-ALPS value of each voxel by three-dimensional voxel-by-voxel calculation, and visualizes the results by assigning pseudo-color to generate an intuitive three-dimensional DTI-ALPS map. In addition, the embodiment of the present application adjusts the step size of the traversal voxels, and realizes DTI-ALPS maps with a step size of one voxel (i.e., a value is calculated for each voxel separately), a step size of two voxels (i.e., a value is calculated for every 2×2×2 voxels), and a step size of three voxels (i.e., a value is calculated for every 3×3×3 voxels), thereby providing a flexible evaluation method at different resolutions for the study. The embodiment of the present application was verified in a data set of 304 subjects. The results showed that the proposed method for generating the DTI-ALPS map revealed more differential areas, and the DTI-ALPS maps with different spatial resolutions were able to show different distinguishing abilities at different stages of the process, indicating that the spatial resolution of the DTI-ALPS map can be flexibly adjusted according to clinical needs, thereby effectively observing the differences between different groups. These results further verify the feasibility and data analysis potential of the method of the present invention.

[0131] See also Figure 8 The present application also provides a DTI-ALPS map generation system that can implement the above-mentioned DTI-ALPS map generation method. The system includes:

[0132] The first module 801 is used to acquire a medical image, perform fiber mapping calculation processing on the medical image, and obtain a fiber diffusivity value;

[0133] The second module 802 is configured to perform region of interest positioning processing on the medical image to obtain a reference region of interest;

[0134] The third module 803 is configured to perform three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions;

[0135] The fourth module 804 is configured to perform pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image.

[0136] It can be understood that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0137] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method for generating a DTI-ALPS map. The electronic device can be any smart terminal, such as a tablet computer or an in-vehicle computer.

[0138] It can be understood that the contents of the above method embodiments are applicable to the present device embodiments, the functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0139] See also Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:

[0140] The processor 901 can be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0141] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called by the processor 901 to execute a method for generating a DTI-ALPS map in the embodiments of this application.

[0142] Input / output interface 903, used to implement information input and output;

[0143] Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0144] Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 );

[0145] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0146] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned method for generating a DTI-ALPS mapping image.

[0147] It can be understood that the contents of the above method embodiments are all applicable to the present storage medium embodiment, the functions specifically implemented by the present storage medium embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0148] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0149] The embodiments of the present application provide a method, system, electronic device and storage medium for generating a DTI-ALPS mapping diagram. The solution obtains a medical image, performs fiber mapping calculation processing on the medical image, and obtains a fiber diffusion rate value, which can provide a calculation basis for subsequent index calculation. In addition, the solution obtains a reference region of interest by performing region of interest positioning processing on the medical image; performs three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image based on the fiber diffusion rate value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions, and can perform coverage calculation on the nerve fibers in the medical image based on the diffusion rate data, and can generate DTI-ALPS mapping diagrams of different spatial resolutions. Moreover, the solution performs pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping diagram, which can more intuitively display the DTI-ALPS index.

[0150] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0151] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0152] The system embodiment described above is merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0153] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0154] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0155] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0156] In the several embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the above units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0157] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0158] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0159] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store programs.

[0160] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A method for generating a DTI-ALPS map, characterized in that: The method comprises the following steps: Acquiring a medical image, performing fiber mapping calculation processing on the medical image, and obtaining a fiber diffusivity value; performing region of interest positioning processing on the medical image to obtain a reference region of interest; Performing three-dimensional voxel-by-voxel computation on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions; The medical image is subjected to pseudo-color display processing according to the DTI-ALPS index to obtain a mapping image.

2. The method according to claim 1, characterized in that The performing of fiber mapping calculation processing on the medical image to obtain the fiber diffusivity value comprises the following steps: performing preprocessing and registration processing on the medical image to obtain a diffusion component map; performing positioning processing on the medical image based on a fiber bundle template to obtain a fiber map; The diffusion component map and the fiber map are multiplied to obtain the fiber diffusivity value.

3. The method according to claim 1, characterized in that The step of performing three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices with different spatial resolutions includes the following steps: Positioning the nerve fibers according to a preset voxel step size to obtain a target region of interest; Performing index calculation processing on the target region of interest and the reference region of interest according to the fiber diffusivity value to obtain a DTI-ALPS index corresponding to the preset voxel step size; The preset voxel step size is adjusted, and the process returns to the process of positioning the nerve fibers according to the preset voxel step size, until the adjustment of the preset voxel step size is completed, thereby obtaining DTI-ALPS indices with different spatial resolutions.

4. The method according to claim 3, characterized in that The step of performing index calculation processing on the target region of interest and the reference region of interest according to the fiber diffusivity value to obtain a DTI-ALPS index corresponding to the preset voxel step size includes the following steps: Determine the projection fiber region of interest and the contact fiber region of interest according to the reference region of interest; determining projection fiber voxels and contact fiber voxels according to the target region of interest; performing index calculation processing on the connection fiber voxel according to the fiber diffusivity value and the projected fiber region of interest to obtain a connection fiber voxel index value; performing index calculation processing on the projected fiber voxel according to the fiber diffusivity value and the connection fiber region of interest to obtain a projected fiber voxel index value; The DTI-ALPS index is obtained according to the connection fiber voxel index value and the projection fiber voxel index value.

5. The method according to claim 4, characterized in that The step of performing index calculation processing on the connection fiber voxel according to the fiber diffusivity value and the projected fiber region of interest to obtain a connection fiber voxel index value comprises the following steps: Calculating and processing the connection fiber voxel according to the fiber diffusivity value to obtain a first direction diffusivity value and a second direction diffusivity value; Calculating and processing the projected fiber region of interest according to the fiber diffusivity value to obtain a first diffusivity value and a second diffusivity value; performing an average calculation process on the first-directional diffusivity value and the first diffusivity value to obtain a first average value; performing an average calculation process on the second-direction diffusivity value and the second diffusivity value to obtain a second average value; A ratio calculation process is performed on the first average value and the second average value to obtain the connection fiber voxel index value.

6. The method according to claim 4, characterized in that The step of performing index calculation processing on the projected fiber voxel according to the fiber diffusivity value and the contact fiber region of interest to obtain a projected fiber voxel index value comprises the following steps: Calculating and processing the connection fiber voxel according to the fiber diffusivity value to obtain a third direction diffusivity value and a fourth direction diffusivity value; Calculating and processing the projected fiber region of interest according to the fiber diffusivity value to obtain a third diffusivity value and a fourth diffusivity value; performing an average calculation process on the third-direction diffusivity value and the third diffusivity value to obtain a third average value; performing average calculation processing on the fourth-direction diffusivity value and the fourth diffusivity value to obtain a fourth average value; A ratio calculation process is performed on the third average value and the fourth average value to obtain the projected fiber voxel index value.

7. The method according to any one of claims 1 to 6, characterized in that The method of performing pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image includes the following steps: Performing format conversion processing on the medical image according to the DTI-ALPS index to obtain a standard format image; Performing color image conversion processing on the standard format image to obtain the mapping image.

8. A DTI-ALPS map generation system, characterized in that: The system comprises: The first module is used to acquire a medical image, perform fiber mapping calculation processing on the medical image, and obtain a fiber diffusivity value; The second module is used to perform region of interest positioning processing on the medical image to obtain a reference region of interest; A third module is configured to perform three-dimensional voxel-by-voxel calculation processing on the nerve fibers in the medical image according to the fiber diffusivity value and the reference region of interest to obtain DTI-ALPS indices of different spatial resolutions; The fourth module is used to perform pseudo-color display processing on the medical image according to the DTI-ALPS index to obtain a mapping image.

9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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