Medical image display method, device, equipment and medium based on multi-directional contour

Abstract

This application relates to a method, apparatus, device, and medium for displaying medical images based on multi-directional contours. The method includes: acquiring an original image sequence; stacking the image data of each image into a cubic data model; establishing a three-dimensional image data field; creating multiple view windows, wherein the multiple view windows are used to display any cross-sectional information in the three-dimensional data field from multiple angles; establishing a local view coordinate system corresponding to each view window and a global coordinate system corresponding to the three-dimensional image data field, wherein each local view coordinate system and the global coordinate system are associated through a transformation matrix, the transformation matrix is ​​used to determine the spatial position of each vertex of each view window in the three-dimensional image data field; responding to a user's adjustment operation on the cross-sectional position of a target view window, based on the transformation matrix, acquiring the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional data field, and displaying the cross-sectional image in the target view window.

Description

Technical Field

[0001] This application relates to the field of medical image processing technology, and in particular to a method, apparatus, device and medium for displaying medical images based on multi-directional contours. Background Technology

[0002] Multi-planar Reconstruction (MPR) allows for the display and adjustment of arbitrary cross-sections, a crucial application in medical imaging software. It can present the characteristics of local areas from multiple angles, enabling clinicians to obtain physiological or pathological information about patients from multiple perspectives, thereby improving diagnostic accuracy.

[0003] In related technologies, to display or capture 3D images, developers need to use C or C++, or supplemented by specialized computer graphics libraries such as OpenGL or Direct3D, to develop a standalone application. If these tasks are processed in memory, due to CPU architecture limitations, it is necessary to traverse every sampling point within the cross-section, perform coordinate transformations, and then map them to the original dataset for sampling or interpolation. Therefore, even with multithreading, the real-time performance of the interaction remains low. Thus, improving the real-time performance of the interaction is a pressing issue that needs to be addressed. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, or at least partially solve the above-mentioned technical problems, this application provides a medical image display method, device, equipment and medium based on multi-directional contour.

[0005] In a first aspect, this application provides a medical image display method based on multi-directional contours, the method comprising:

[0006] The original image sequence is obtained, and the image data of each image is stacked into a cube data model to establish a three-dimensional image data field.

[0007] Multiple view windows are created; these multiple view windows are used to display any cross-sectional information in the three-dimensional image data field from multiple angles.

[0008] A local view coordinate system corresponding to each view window and a global coordinate system corresponding to the three-dimensional image data field are established respectively; wherein, each local view coordinate system and the global coordinate system are associated with each other through a transformation matrix, the transformation matrix is ​​used to transform each vertex of each view window to the global coordinate system, so as to determine the spatial position of each vertex of each view window in the three-dimensional image data field;

[0009] In response to the user's operation to adjust the cross-sectional position of the target view window, based on the transformation matrix, the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field are obtained, and the cross-sectional image is displayed in the target view window.

[0010] As an optional implementation of this invention, the step of establishing the local view coordinate system corresponding to each view window and the global coordinate system corresponding to the three-dimensional image data field includes:

[0011] With the top left corner of each view window as the origin, establish the local view coordinate system for the plane coordinate system where each view window is located;

[0012] Using one vertex of the three-dimensional image data field as the origin, and based on the right-hand rule, the spatial coordinate system where the three-dimensional image data field is located is established as the global coordinate system.

[0013] As an optional implementation of this invention, the step of responding to a user's angle adjustment operation on the target view window, obtaining the pixel values ​​corresponding to the cross-sectional image of the target view window in the three-dimensional image data field based on the transformation matrix, and displaying the cross-sectional image in the target view window includes:

[0014] In response to the user's angle adjustment operation on the target view window, determine the cross-sectional image;

[0015] The data field composed of the coordinates of all points in the cross-sectional image is used to construct a two-dimensional matrix;

[0016] Based on the two-dimensional matrix and the transformation matrix, obtain the coordinate transformation results of all points;

[0017] The coordinate transformation results of all points are normalized to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0018] As an optional embodiment of the present invention, the step of constructing a two-dimensional matrix from the data field composed of the coordinates of all points in the cross-sectional image includes:

[0019] For each point to be transformed in the cross-sectional image, the coordinates of each point to be transformed are used to construct a column vector;

[0020] The data field composed of all column vectors is formed into a two-dimensional matrix.

[0021] As an optional implementation of this invention, the normalization processing of the coordinate transformation results of all points to obtain the pixel values ​​corresponding to the cross-sectional image of the target view window in the three-dimensional image data field includes:

[0022] The coordinate transformation results of all points are scale-normalized to obtain the texture coordinates of all points;

[0023] The texture coordinates of all points are input into the fragment shader to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0024] As an optional implementation of this invention, the cross-sectional position adjustment operation includes:

[0025] Browse by turning pages in the target view window;

[0026] or;

[0027] Drag the crosshair in the target view window to rotate or translate;

[0028] or;

[0029] Click on the target location in the target view window to perform multi-view association positioning.

[0030] Secondly, this application provides a medical imaging display device based on multi-directional contours, comprising:

[0031] The image import module is used to acquire the original image sequence, stack the image data of each image into a cube data model, and establish a three-dimensional image data field.

[0032] A view display module is used to create multiple view windows; the multiple view windows are used to display any cross-sectional information in the three-dimensional image data field from multiple angles.

[0033] The coordinate system establishment module is used to establish a local view coordinate system corresponding to each view window and a global coordinate system corresponding to the three-dimensional image data field, respectively; wherein, each local view coordinate system is associated with the global coordinate system through a transformation matrix, the transformation matrix is ​​used to transform each vertex of each view window into the global coordinate system, so as to determine the spatial position of each vertex of each view window in the three-dimensional image data field;

[0034] The image acquisition module is used to respond to the user's operation of adjusting the cross-sectional position of the target view window, acquire the corresponding pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field based on the transformation matrix, and display the cross-sectional image in the target view window.

[0035] As an optional implementation of this invention, the coordinate system establishment module is specifically used for:

[0036] With the top left corner of each view window as the origin, establish the local view coordinate system for the plane coordinate system where each view window is located;

[0037] Using one vertex of the three-dimensional image data field as the origin, and based on the right-hand rule, the spatial coordinate system where the three-dimensional image data field is located is established as the global coordinate system.

[0038] As an optional implementation of this invention, the image acquisition module includes:

[0039] The response unit is used to determine the cross-sectional image in response to the user's angle adjustment operation on the target view window;

[0040] A construction unit is used to construct a two-dimensional matrix from the data field composed of the coordinates of all points in the cross-sectional image;

[0041] The acquisition unit is used to acquire the coordinate transformation results of all points based on the two-dimensional matrix and the transformation matrix;

[0042] The processing unit is used to normalize the coordinate transformation results of all points to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0043] As an optional implementation of this invention, the building unit is specifically used for:

[0044] For each point to be transformed in the cross-sectional image, the coordinates of each point to be transformed are used to construct a column vector;

[0045] The data field composed of all column vectors is formed into a two-dimensional matrix.

[0046] As an optional implementation of this invention, the processing unit is specifically used for:

[0047] The coordinate transformation results of all points are scale-normalized to obtain the texture coordinates of all points;

[0048] The texture coordinates of all points are input into the fragment shader to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0049] As an optional implementation of this invention, the cross-sectional position adjustment operation includes:

[0050] Browse by turning pages in the target view window;

[0051] or;

[0052] Drag the crosshair in the target view window to rotate or translate;

[0053] or;

[0054] Click on the target location in the target view window to perform multi-view association positioning.

[0055] Thirdly, this application provides a computer device including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method provided in the first aspect of this application.

[0056] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect of this application.

[0057] The technical solution provided in this application has the following advantages compared with the prior art:

[0058] This application provides a medical image display method based on multi-directional contours. It acquires the original image sequence, stacks the image data of each image into a cubic data model to establish a three-dimensional image data field, and creates multiple view windows. These view windows are used to display any cross-sectional information in the three-dimensional data field from multiple angles. A local view coordinate system and a global coordinate system corresponding to the three-dimensional image data field are established for each view window. In response to user adjustments to the cross-sectional position of the target view window, the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional data field are obtained based on a transformation matrix, and the cross-sectional image is displayed in the target view window. Since each local view coordinate system is associated with the global coordinate system through a transformation matrix, and the transformation matrix is ​​used to transform each vertex of each view window to the global coordinate system to determine the spatial position of each vertex in the three-dimensional image data field, batch pixel calculations can be performed through the transformation matrix. Based on a GPU-based parallel architecture design, all calculations can be completed in a single parallel operation per unit time, avoiding the inefficiency caused by traversing every sampling point within the cross-section when dealing with a large number of pixels, thereby improving real-time interactivity. Attached Figure Description

[0059] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0060] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0061] Figure 1 This is a flowchart illustrating a medical image display method based on multi-directional contours in one embodiment;

[0062] Figure 2 This is a schematic diagram illustrating the coordinate system transformation principle of a medical image display method based on multi-directional contours in one embodiment;

[0063] Figure 3 This is a schematic diagram illustrating the normalization from the image coordinate system to the texture coordinate system in one embodiment;

[0064] Figure 4 This is a schematic diagram of a medical image display with multi-directional contours in one embodiment;

[0065] Figure 5 This is a schematic diagram of the structure of a medical imaging display device based on multi-directional contours in one embodiment;

[0066] Figure 6 This is a schematic diagram of the structure of a computer device in one embodiment. Detailed Implementation

[0067] To better understand the above-mentioned objectives, features, and advantages of this application, the solution of this application will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0068] Many specific details are set forth in the following description in order to provide a full understanding of this application, but this application may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some embodiments of this application, and not all embodiments.

[0069] WebGL (Web Graphics Library) is a technology used to draw and render complex 3D graphics on web pages and allow users to interact with them. WebGL combines HTML5 and JavaScript, allowing developers to create and render 3D graphics or images on web pages. It is embedded in the browser, requiring no plugins or libraries, and can be used directly; moreover, because it is browser-based rather than operating system-based, it can run on multiple platforms, such as personal computers or mobile smart devices.

[0070] In one embodiment, such as Figure 1 As shown, a medical image display method based on multi-directional contours is provided. This method can be applied to products using a B / S (browser / server) architecture for medical image viewing and annotation. In this embodiment, the method includes the following steps:

[0071] S11. Obtain the original image sequence, stack the image data of each image into a cube data model, and establish a three-dimensional image data field.

[0072] Imaging sequences refer to a series of two-dimensional images that change over time or space, acquired using different imaging parameters or techniques during examinations such as magnetic resonance imaging (MRI) or computed tomography (CT). These sequences can reveal different features of body tissues and structures, helping doctors diagnose diseases more accurately.

[0073] Specifically, the raw image sequence can be obtained from a backend server or from local storage. After acquiring the raw image sequence, the data from each image is stacked into a cubic data model to establish a three-dimensional image data field. A three-dimensional image data field typically refers to a set of data points distributed in three-dimensional space. These data points can be scalar values, vector values, or more complex data structures. This data often includes galactic images of the internal structure of the human body. In this case, each point in the data field corresponds to a voxel in the scanned volume. A voxel is short for "volume pixel," which represents a small cubic unit in three-dimensional space, similar to a pixel in a two-dimensional image.

[0074] S12. Create multiple view windows.

[0075] The plurality of view windows are used to display any cross-sectional information in the three-dimensional image data field from multiple angles.

[0076] Specifically, three view windows are created to present cross-sectional information of the three-dimensional image data field from three different orientations. These three orientations are the coronal, sagittal, and axial views. The coronal view is a longitudinal section along the left-right direction of the body, dividing it into anterior and posterior sections. In cardiac or chest CT scans, coronal images show the arrangement of structures from the front of the sternum to the back. The sagittal view is a longitudinal section along the front-back direction of the body, dividing it into two symmetrical parts. For example, in head or spine imaging, common sagittal images show continuous lateral views of the left and right cerebral hemispheres or the spine. The axial plane, also known as a transverse or horizontal plane, is a term in medical imaging referring to a section parallel to the ground, similar to a slice taken from the top of the head to the bottom. Axial images allow observation of cross-sections of internal body structures, which is crucial for radiologists and other medical professionals to interpret image information, aiding in accurate disease diagnosis and treatment planning. These three planes are essential for radiologists and other medical professionals to interpret image information, aiding in accurate disease diagnosis and treatment planning. For example, in DICOM image viewing software, users can usually freely rotate 3D image data to view images with different cross-sections.

[0077] All three view windows provide users with the ability to manipulate the MPR crosshairs. The MPR crosshairs are used to pinpoint the specific locations of the other two views within a single view. The MPR crosshairs are virtual lines in the MPR view used for locating and cutting the image. They typically consist of two lines, a vertical and a horizontal line, which intersect at the center of the image, helping users select and view specific areas of the image. MPR often involves the display of multiple views, such as axial, coronal, and sagittal planes. The crosshairs can be synchronized across these views to provide comprehensive image information.

[0078] S13. Establish the local view coordinate system corresponding to each view window and the global coordinate system corresponding to the three-dimensional image data field respectively.

[0079] Each local view coordinate system is associated with the global coordinate system through a transformation matrix. The transformation matrix is ​​used to transform each vertex of each view window into the global coordinate system to determine the spatial position of each vertex of each view window in the three-dimensional image data field.

[0080] In some embodiments, step S13 (establishing the local view coordinate system corresponding to each view window and the global coordinate system corresponding to the three-dimensional image data field) can be implemented in the following way:

[0081] With the top left corner of each view window as the origin, establish the local view coordinate system for the plane coordinate system where each view window is located;

[0082] Using one vertex of the three-dimensional image data field as the origin, and based on the right-hand rule, the spatial coordinate system where the three-dimensional image data field is located is established as the global coordinate system.

[0083] Specifically, for ease of calculation, this disclosure proposes four coordinate systems: three local view coordinate systems and one global coordinate system. The three local view coordinate systems are constructed with the top-left corner of each view window as the origin, the rightward direction as the positive x-axis, the downward direction as the positive y-axis, and the positive z-axis following a right-hand rule. The global coordinate system is established with a vertex of the original 3D image data field as the origin, using a right-hand rule. The global coordinate system and the three local view coordinate systems constitute a four-system system. Each local view coordinate system is associated with the global coordinate system by a transformation matrix, used to transform the four corner vertices of the view window to the global system to determine their spatial position in the 3D image data field.

[0084] S14. In response to the user's operation to adjust the cross-sectional position of the target view window, based on the transformation matrix, obtain the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field, and display the cross-sectional image in the target view window.

[0085] The section position adjustment operation includes: browsing through pages in the target view window; or: dragging the crosshair in the target view window to rotate or translate; or: clicking on the target position in the target view window to perform multi-view association positioning.

[0086] MPR crosshairs allow users to interact with images, such as panning and rotating, to observe lesions or other anatomical structures from different angles. By adjusting the position of the crosshairs, users can cut out the desired two-dimensional image at any location in three-dimensional space, facilitating the analysis of irregularly shaped lesions or organs.

[0087] Specifically, the interactive page provides users with the ability to manipulate the crosshair to adjust the position of other sections relative to the current section. The provided interactive operations include: scrolling the mouse wheel through a single view window; dragging the crosshair in the view window to rotate or pan, while simultaneously resampling and displaying other views; and clicking on a location in the view window to perform three-view repositioning, etc.

[0088] In some embodiments, step S14 (in response to a user's operation to adjust the cross-sectional position of the target view window, obtaining the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field based on the transformation matrix, and displaying the cross-sectional image in the target view window) can be implemented in the following way:

[0089] A. In response to the user's angle adjustment operation on the target view window, determine the cross-sectional image.

[0090] B. Construct a two-dimensional matrix from the data field formed by the coordinates of all points in the cross-sectional image.

[0091] In some embodiments, step B above (constructing a two-dimensional matrix from the data field composed of the coordinates of all points in the cross-sectional image) can be implemented in the following way:

[0092] For each point to be transformed in the cross-sectional image, the coordinates of each point to be transformed are used to construct a column vector;

[0093] The data field composed of all column vectors is formed into a two-dimensional matrix.

[0094] C. Based on the two-dimensional matrix and the transformation matrix, obtain the coordinate transformation results of all points.

[0095] Specifically, refer to Figure 2As shown, the global coordinate system OXYZ is the spatial coordinate system where the 3D image data is located, and the local coordinate system O'X'Y'Z' is the Cartesian coordinate system where the view window is located. The relationship between the two can be established by a transformation matrix M. The structure of M is shown below:

[0096]

[0097] Where R is the rotation subarray, representing the spatial orientation of the three coordinate axes in the local coordinate system O'X'Y'Z' in the global coordinate system OXYZ. The R component defines the rotational attitude of the local coordinate system O'X'Y'Z' in the global coordinate system OXYZ. T is the translation subarray, representing the spatial coordinates of O' as observed in the global coordinate system OXYZ.

[0098] The view window directly displays the final cross-sectional image. Each pixel value in the cross-sectional image is obtained from the 3D image data field. Therefore, sampling calculation involves taking each pixel in the view window and using its local coordinate system O'X'Y'Z' as a starting point, to calculate its corresponding coordinates in the global coordinate system OXYZ. The specific calculation process for a single pixel is as follows:

[0099]

[0100] For all pixels within the cross-sectional image, the above calculation process needs to be repeated. Traditional calculation methods are inefficient when dealing with a large number of pixels, especially in scenarios with high algorithmic requirements, such as interactive classes. Therefore, in this embodiment, the coordinate transformation process is replaced by matrix-vector operations, and the batch pixel calculation process is as follows:

[0101]

[0102] For the coordinate transformation process, the coordinates of the point to be transformed are formed into a column vector, and the data field composed of all the point coordinates is formed into a two-dimensional matrix. This matrix is ​​then input as a two-dimensional texture into the fragment shader. Simultaneously, the transformation matrices, trigger conditions, and an empty texture are also input to store the calculation results. The transformation process is written in the fragment shader's main function. Thus, the output after one texture calculation contains the coordinate transformation results of all points.

[0103] The advantage of this approach is that, based on the parallel architecture design of GPUs, all calculations can be completed in a single parallel operation per unit time. Moreover, the number of units supported by this parallel operation is much higher than that of CPU programs. Therefore, even when the demand expands and requires a large number of custom flat-panel display interface images, the processing time will not be extended.

[0104] D. Normalize the coordinate transformation results of all points to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0105] In some embodiments, step D (normalizing the coordinate transformation results of all points to obtain the pixel values ​​corresponding to the cross-sectional image of the target view window in the three-dimensional image data field) can be implemented in the following way:

[0106] The coordinate transformation results of all points are scale-normalized to obtain the texture coordinates of all points;

[0107] The texture coordinates of all points are input into the fragment shader to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0108] Specifically, for a single view, after the spatial positions of the four corner vertices of the cross-sectional image in the 3D image data field are determined, the view's sampling process is combined with the WEBGL 3D texture. Compared to a 2D texture, the 3D texture data field has an additional depth information; however, the sampling process is similar, so the original data field can be constructed into a 3D texture.

[0109] 3D textures are a feature of WebGL that allows developers to create and render 3D images using 3D data. These textures can be used to store large amounts of data, such as medical image sequences. It is a texture object containing multiple 2D texture layers, each stacked in the depth direction. Its texture coordinates are represented by a 3D vector (u, v, w), where w represents the coordinate in the depth direction. Compared to CPU programs, it can capture more details and information in 3D space, achieving smooth 3D transitions and gradients. It is suitable for rendering and visualizing complex 3D datasets. Furthermore, for developers, when presenting 2D image information, they only need to focus on the spatial positioning of the four vertices of the planar 2D image; the internal pixel sampling and interpolation processes are automatically completed by the GPU, simplifying the development process and improving development efficiency. This disclosure proposes a scheme combining WebGL 3D texture sampling technology, which can simultaneously meet the challenges of limited browser computing resources and high real-time interactive requirements, thus improving the user experience.

[0110] For example, after scaling the coordinate transformation results (i.e., spatial coordinates) of all the points calculated above, they are converted into texture coordinates, as shown in the example. Figure 3 As shown; by inputting all texture coordinates into the fragment shader, the GPU can perform rendering processing, displaying the cross-sectional image as grayscale values ​​in the corresponding view window, as shown. Figure 4As shown, the top left, bottom left, and top right corners display the MPR three-view diagram, while the bottom right corner shows the 3D image data field, rendered using volume rendering. Volume rendering is a 3D data visualization technique that generates 2D images by simulating light rays passing through a 3D image data field (such as volume data obtained from medical imaging CT or MRI scans), thereby displaying the internal structure and features of an object. Volume rendering can provide more information than traditional 2D slice images because it allows data to be observed from multiple angles and depths.

[0111] This application provides a medical image display method based on multi-directional contours. It acquires the original image sequence, stacks the image data of each image into a cubic data model to establish a three-dimensional image data field, and creates multiple view windows. These view windows are used to display any cross-sectional information in the three-dimensional data field from multiple angles. A local view coordinate system and a global coordinate system corresponding to the three-dimensional image data field are established for each view window. In response to user adjustments to the cross-sectional position of the target view window, the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional data field are obtained based on a transformation matrix, and the cross-sectional image is displayed in the target view window. Since each local view coordinate system is associated with the global coordinate system through a transformation matrix, and the transformation matrix is ​​used to transform each vertex of each view window to the global coordinate system to determine the spatial position of each vertex in the three-dimensional image data field, batch pixel calculations can be performed through the transformation matrix. Based on a GPU-based parallel architecture design, all calculations can be completed in a single parallel operation per unit time, avoiding the inefficiency caused by traversing every sampling point within the cross-section when dealing with a large number of pixels, thereby improving real-time interactivity.

[0112] In one embodiment, such as Figure 5 As shown, a medical imaging display device 500 based on multi-directional contours is provided, comprising:

[0113] The image import module 510 is used to acquire the original image sequence, stack the image data of each image into a cube data model, and establish a three-dimensional image data field.

[0114] The view display module 520 is used to create multiple view windows; the multiple view windows are used to display any cross-sectional information in the three-dimensional image data field from multiple angles.

[0115] The coordinate system establishment module 530 is used to establish a local view coordinate system corresponding to each view window and a global coordinate system corresponding to the three-dimensional image data field, respectively; wherein, each local view coordinate system is associated with the global coordinate system through a transformation matrix, the transformation matrix is ​​used to transform each vertex of each view window into the global coordinate system, so as to determine the spatial position of each vertex of each view window in the three-dimensional image data field.

[0116] The image acquisition module 540 is used to respond to the user's operation of adjusting the cross-sectional position of the target view window, acquire the corresponding pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field based on the transformation matrix, and display the cross-sectional image in the target view window.

[0117] As an optional implementation of this invention, the coordinate system establishment module is specifically used for:

[0118] With the top left corner of each view window as the origin, establish the local view coordinate system for the plane coordinate system where each view window is located;

[0119] Using one vertex of the three-dimensional image data field as the origin, and based on the right-hand rule, the spatial coordinate system where the three-dimensional image data field is located is established as the global coordinate system.

[0120] As an optional implementation of this invention, the image acquisition module includes:

[0121] The response unit is used to determine the cross-sectional image in response to the user's angle adjustment operation on the target view window;

[0122] A construction unit is used to construct a two-dimensional matrix from the data field composed of the coordinates of all points in the cross-sectional image;

[0123] The acquisition unit is used to acquire the coordinate transformation results of all points based on the two-dimensional matrix and the transformation matrix;

[0124] The processing unit is used to normalize the coordinate transformation results of all points to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0125] As an optional implementation of this invention, the building unit is specifically used for:

[0126] For each point to be transformed in the cross-sectional image, the coordinates of each point to be transformed are used to construct a column vector;

[0127] The data field composed of all column vectors is formed into a two-dimensional matrix.

[0128] As an optional implementation of this invention, the processing unit is specifically used for:

[0129] The coordinate transformation results of all points are scale-normalized to obtain the texture coordinates of all points;

[0130] The texture coordinates of all points are input into the fragment shader to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

[0131] As an optional implementation of this invention, the cross-sectional position adjustment operation includes:

[0132] Browse by turning pages in the target view window;

[0133] or;

[0134] Drag the crosshair in the target view window to rotate or translate;

[0135] or;

[0136] Click on the target location in the target view window to perform multi-view association positioning.

[0137] This application provides a medical image display device based on multi-directional contours. It acquires original image sequences, stacks the image data of each image into a cubic data model, establishes a three-dimensional image data field, and creates multiple view windows. These view windows are used to display any cross-sectional information in the three-dimensional data field from multiple angles. A local view coordinate system and a global coordinate system corresponding to the three-dimensional image data field are established for each view window. In response to user adjustments to the cross-sectional position of the target view window, the device uses a transformation matrix to obtain the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional data field and displays the cross-sectional image in the target view window. Since each local view coordinate system is associated with the global coordinate system through a transformation matrix, and the transformation matrix transforms each vertex of each view window to the global coordinate system to determine the spatial position of each vertex in the three-dimensional image data field, batch pixel calculations can be performed using the transformation matrix. Based on a GPU-based parallel architecture, all calculations can be completed in a single parallel operation per unit time, avoiding the inefficiency caused by traversing every sampling point within the cross-section when dealing with a large number of pixels, thereby improving real-time interaction.

[0138] Specific limitations regarding the multi-directional contour-based medical imaging display device can be found in the above section on the limitations of applying the multi-directional contour-based medical imaging display method to computer equipment, and will not be repeated here. Each module in the aforementioned multi-directional contour-based medical imaging display device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in hardware or independently of the processor in the computer device, or stored in software in the memory of the computer device, so that the processor can call and execute the operations corresponding to each module.

[0139] In one embodiment, a computer device is provided, the internal structure of which can be shown as follows: Figure 6 As shown. The computer device includes a processor 61 and a memory 62 connected via a system bus. The processor 61 provides computing and control capabilities. The memory 62 includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. When the computer program is executed by the processor, it implements a medical image display method based on multi-directional contours. The display screen of the computer device can be a liquid crystal display (LCD) or an electronic ink display. The input device of the computer device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse, etc.

[0140] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0141] In one embodiment, the multi-directional contour-based medical image display method provided in this application can be implemented as a computer program, which can be implemented in, for example... Figure 6 The computer device shown is running on this device. The computer device's memory can store the various program modules that make up the mobile terminal of the computer device, for example, Figure 5 The image import module 510, view display module 520, coordinate system establishment module 530, and image acquisition module 540 are shown. The computer program comprised of these modules causes the processor to execute the steps in the multi-directional contour-based medical image display method of the computer device described in the various embodiments of this application.

[0142] For example, Figure 6The computer equipment shown can be used as follows Figure 5 The image import module 510 in the multi-directional contour-based medical imaging display device shown executes step S11. The computer device can execute step S12 via the view display module 520. The computer device can execute step S13 via the coordinate system establishment module. The computer device can execute step S14 via the image acquisition module 540.

[0143] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0144] Those skilled in the art will understand that implementing all or part of the processes in the above-described example methods can be accomplished by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include ROM (Read-Only Memory), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include RAM (Random Access Memory) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as SRAM (Static Random Access Memory) and DRAM (Dynamic Random Access Memory), etc.

[0145] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0146] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A medical image display method based on multi-directional contours, characterized in that, The method includes: The original image sequence is obtained, and the image data of each image is stacked into a cube data model to establish a three-dimensional image data field. Multiple view windows are created; these multiple view windows are used to display any cross-sectional information in the three-dimensional image data field from multiple angles. A local view coordinate system corresponding to each view window and a global coordinate system corresponding to the three-dimensional image data field are established respectively; wherein, each local view coordinate system and the global coordinate system are associated with each other through a transformation matrix, the transformation matrix is ​​used to transform each vertex of each view window to the global coordinate system, so as to determine the spatial position of each vertex of each view window in the three-dimensional image data field; In response to the user's operation to adjust the cross-sectional position of the target view window, based on the transformation matrix, the pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field are obtained, and the cross-sectional image is displayed in the target view window; The step of responding to a user's angle adjustment operation on a target view window, based on the transformation matrix, obtaining the pixel values ​​corresponding to the cross-sectional image of the target view window in the three-dimensional image data field, and displaying the cross-sectional image in the target view window includes: In response to the user's angle adjustment operation on the target view window, determine the cross-sectional image; The data field composed of the coordinates of all points in the cross-sectional image is used to construct a two-dimensional matrix; Based on the two-dimensional matrix and the transformation matrix, obtain the coordinate transformation results of all points; The coordinate transformation results of all points are normalized to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

2. The method according to claim 1, characterized in that, The step of establishing the local view coordinate system corresponding to each view window and the global coordinate system corresponding to the three-dimensional image data field includes: With the top left corner of each view window as the origin, establish the local view coordinate system for the plane coordinate system where each view window is located; Using one vertex of the three-dimensional image data field as the origin, and based on the right-hand rule, the spatial coordinate system where the three-dimensional image data field is located is established as the global coordinate system.

3. The method according to claim 1, characterized in that, The step of constructing a two-dimensional matrix from the data field composed of the coordinates of all points in the cross-sectional image includes: For each point to be transformed in the cross-sectional image, the coordinates of each point to be transformed are used to construct a column vector; The data field composed of all column vectors is formed into a two-dimensional matrix.

4. The method according to claim 1, characterized in that, The normalization process for the coordinate transformation results of all points yields the pixel values ​​corresponding to the cross-sectional image of the target view window in the three-dimensional image data field, including: The coordinate transformation results of all points are scale-normalized to obtain the texture coordinates of all points; The texture coordinates of all points are input into the fragment shader to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

5. The method according to claim 1, characterized in that, The cross-sectional position adjustment operation includes: Browse by turning pages in the target view window; or; Drag the crosshair in the target view window to rotate or translate; or; Click on the target location in the target view window to perform multi-view association positioning.

6. A medical imaging display device based on multi-directional contours, characterized in that, include: The image import module is used to acquire the original image sequence, stack the image data of each image into a cube data model, and establish a three-dimensional image data field. A view display module is used to create multiple view windows; the multiple view windows are used to display any cross-sectional information in the three-dimensional image data field from multiple angles. The coordinate system establishment module is used to establish a local view coordinate system corresponding to each view window and a global coordinate system corresponding to the three-dimensional image data field, respectively; wherein, each local view coordinate system is associated with the global coordinate system through a transformation matrix, the transformation matrix is ​​used to transform each vertex of each view window into the global coordinate system, so as to determine the spatial position of each vertex of each view window in the three-dimensional image data field; The image acquisition module is used to respond to the user's operation of adjusting the cross-sectional position of the target view window, acquire the corresponding pixel values ​​of the cross-sectional image at the cross-sectional position in the three-dimensional image data field based on the transformation matrix, and display the cross-sectional image in the target view window; The image acquisition module is specifically used for: In response to the user's angle adjustment operation on the target view window, determine the cross-sectional image; The data field composed of the coordinates of all points in the cross-sectional image is used to construct a two-dimensional matrix; Based on the two-dimensional matrix and the transformation matrix, obtain the coordinate transformation results of all points; The coordinate transformation results of all points are normalized to obtain the pixel values ​​of the cross-sectional image of the target view window in the three-dimensional image data field.

7. The apparatus according to claim 6, characterized in that, The coordinate system establishment module is specifically used for: With the top left corner of each view window as the origin, establish the local view coordinate system for the plane coordinate system where each view window is located; Using one vertex of the three-dimensional image data field as the origin, and based on the right-hand rule, the spatial coordinate system where the three-dimensional image data field is located is established as the global coordinate system.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the medical image display method based on multi-directional contours as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the medical image display method based on multi-directional contours as described in any one of claims 1 to 5.

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