A method for generating a bull's-eye image and related device

Abstract

The present application discloses a method for generating a bull's-eye diagram and a related device, which relate to the field of medical image recognition technology. The method includes determining a multi-frame horizontal long-axis image, a multi-frame vertical long-axis image, and a multi-frame short-axis image of the myocardium in a cardiac axis coordinate system; identifying the image to obtain the multi-frame ellipse center, the ellipse long-axis radius of the multi-frame horizontal long-axis image, the ellipse long-axis radius of the multi-frame vertical long-axis image, and the circular radius of the multi-frame short-axis image; based on the identified information, determining the target frame interval in the short-axis direction; based on the short-axis image corresponding to the target frame interval, determining the multi-frame circular ring and the multi-frame myocardial area, and scaling the multi-frame myocardial area to the corresponding frame circular ring to obtain the multi-frame myocardial circular ring, and then determining the bull's-eye diagram of the myocardium. By accurately analyzing and processing the tomographic scan image of a specific frame, the bull's-eye diagram is quickly generated, which reduces the dependence on a large number of samples and improves the efficiency of generating the bull's-eye diagram.

Description

Technical Field

[0001] The present application relates to the technical field of medical image recognition, and in particular to a method for generating a bull's-eye image and related devices. Background Art

[0002] In the field of medical image recognition and analysis, the bull's-eye diagram, as a tool that intuitively displays myocardial metabolism or perfusion, can highlight the difference between estimation and completion, and is crucial for evaluating cardiac function and diagnosing heart disease.

[0003] Currently, the generation of bull's-eye images mainly relies on machine learning technology through learning and analyzing tomographic image samples.

[0004] However, the machine learning process requires collecting and processing a large number of tomography image samples, which is not only time-consuming but also difficult to implement when sample resources are limited. Summary of the Invention

[0005] In view of the above problems, this application provides a method and related device for generating a bull's-eye graph, in order to reduce the dependence on a large number of samples and improve the efficiency of generating the bull's-eye graph. The specific solution is as follows:

[0006] A first aspect of the present application provides a method for generating a bull's-eye graph, characterized by comprising:

[0007] Determining a tomographic image of the myocardium in a cardiac axis coordinate system, wherein the tomographic image of the myocardium in the cardiac axis coordinate system includes multiple frames of horizontal long axis images, multiple frames of vertical long axis images, and multiple frames of short axis images;

[0008] Identifying the multiple frames of horizontal long-axis images, the multiple frames of vertical long-axis images, and the multiple frames of short-axis images to obtain a multi-frame ellipse center, an ellipse long-axis radius of the multiple frames of horizontal long-axis images, an ellipse long-axis radius of the multiple frames of vertical long-axis images, and a circular radius of the multiple frames of short-axis images;

[0009] determining a target frame interval in the short axis direction based on the ellipse major axis radius of the multiple frames of horizontal long axis images, the ellipse major axis radius of the multiple frames of vertical long axis images, the circular radius of the multiple frames of short axis images, and the center of the multiple frames of ellipse;

[0010] Determining a multi-frame annulus and a multi-frame myocardial region based on the acquired number of frames of the target frame interval and the short-axis image corresponding to the target frame interval, and scaling the multi-frame myocardial region to the corresponding annulus of each frame to obtain a multi-frame myocardial annulus;

[0011] Determine the target frame myocardial ring, project the other frame myocardial rings onto the target frame myocardial ring, and convert the projected image into polar coordinates to obtain a bull's eye image of the myocardium, where the center of the outer circle corresponding to the target frame myocardial ring is the apex, and the other frame myocardial rings are the multiple frame myocardial rings in the multiple frame myocardial rings except the target frame myocardial ring.

[0012] In a possible implementation, determining a tomographic image of the myocardium in a cardiac axis coordinate system includes:

[0013] Acquire a tomographic image of the myocardium in a human coordinate system;

[0014] performing coordinate rotation on the tomographic image of the myocardium in the human body coordinate system to obtain a rotated tomographic image;

[0015] Bilinear interpolation is performed on the rotated tomographic image to obtain a tomographic image of the myocardium in a cardiac axis coordinate system.

[0016] In a possible implementation, determining the target frame interval in the short-axis direction based on the ellipse major axis radius of the multiple-frame horizontal long-axis image, the ellipse major axis radius of the multiple-frame vertical long-axis image, the circular radius of the multiple-frame short-axis image, and the center of the multi-frame ellipse includes:

[0017] Acquiring the pixel size of the multiple frames of horizontal long-axis images, the pixel size of the multiple frames of vertical long-axis images, and the inter-slice spacing of the multiple frames of short-axis images;

[0018] Calculating a first frame interval in the short axis direction based on the inter-slice spacing of the multiple-frame short axis images, the pixel size of the multiple-frame horizontal long axis images, and the ellipse major axis radius of the multiple-frame horizontal long axis images;

[0019] Calculating a second frame interval in the short-axis direction based on the inter-slice spacing of the multiple-frame short-axis images, the pixel size of the multiple-frame vertical long-axis images, and the ellipse major axis radius of the multiple-frame vertical long-axis images;

[0020] selecting a larger frame interval between the first frame interval in the short-axis direction and the second frame interval in the short-axis direction as a candidate frame interval in the short-axis direction;

[0021] Based on the circular radius of the multi-frame short-axis images and the center of the multi-frame ellipse, a target frame section in the short-axis direction is determined from the candidate frame sections in the short-axis direction.

[0022] In a possible implementation, determining the target frame interval in the short-axis direction from the candidate frame intervals in the short-axis direction based on the circular radius of the multi-frame short-axis images and the center of the multi-frame ellipse includes:

[0023] Filtering a starting frame in the short-axis direction from the candidate frame interval in the short-axis direction, wherein the vertex of the circular radius of the short-axis image corresponding to the starting frame in the short-axis direction is the apex of the heart;

[0024] Filtering out an end frame in the short-axis direction from the candidate frame intervals in the short-axis direction, wherein the center of the ellipse corresponding to the end frame in the short-axis direction is the heart base;

[0025] A target frame section in the short-axis direction is determined based on the start frame in the short-axis direction and the end frame in the short-axis direction.

[0026] In a possible implementation, determining the multi-frame annulus and the multi-frame myocardial region based on the acquired number of frames of the target frame interval and the short-axis image corresponding to the target frame interval includes:

[0027] Detecting the short-axis image corresponding to the target frame interval to obtain the center and radius of the outer circle of multiple frames;

[0028] Based on the obtained number of frames in the target frame interval and the maximum outer circle radius, a ring width of each frame in the target frame interval is calculated, and based on the ring width of each frame, the corresponding centers of the outer circles of multiple frames and the outer circle radii of the multiple frames are combined to obtain the multi-frame circular ring, wherein the centers of the outer circles of multiple frames of the multi-frame circular ring coincide with each other;

[0029] The short-axis image corresponding to the target frame interval is divided to obtain the multi-frame myocardial region.

[0030] In a possible implementation, the myocardial bull's-eye image includes multiple segments, and the method further includes:

[0031] calculating a standardized uptake value of each of the segments and an average standardized uptake value of the bull's-eye image;

[0032] For each segment, the percentage of the standardized uptake value of the segment to the average standardized uptake value of the bull's-eye image was calculated, and the percentage was used as the score of the segment.

[0033] A second aspect of the present application provides a device for generating a bull's-eye image, characterized by comprising:

[0034] A first determining unit is configured to determine a tomographic image of the myocardium in a cardiac axis coordinate system, wherein the tomographic image of the myocardium in the cardiac axis coordinate system includes multiple frames of horizontal long axis images, multiple frames of vertical long axis images, and multiple frames of short axis images;

[0035] an identification unit, configured to identify the multi-frame horizontal long-axis images, the multi-frame vertical long-axis images, and the multi-frame short-axis images, and obtain a multi-frame ellipse center, an ellipse long-axis radius of the multi-frame horizontal long-axis images, an ellipse long-axis radius of the multi-frame vertical long-axis images, and a circular radius of the multi-frame short-axis images;

[0036] a second determining unit, configured to determine a target frame interval in a minor axis direction based on the ellipse major axis radius of the multiple frames of horizontal major axis images, the ellipse major axis radius of the multiple frames of vertical major axis images, the circular radius of the multiple frames of minor axis images, and the center of the multiple frames of ellipse;

[0037] a third determining unit, configured to determine a multi-frame annulus and a multi-frame myocardial region based on the number of frames acquired in the target frame interval and the short-axis image corresponding to the target frame interval, and scale the multi-frame myocardial region onto the corresponding annulus of each frame to obtain a multi-frame myocardial annulus;

[0038] The fourth determination unit is used to determine the target frame myocardial ring, project the myocardial rings of other frames onto the target frame myocardial ring, and convert the image obtained after projection into polar coordinates to obtain a bull's eye image of the myocardium, the center of the outer circle corresponding to the target frame myocardial ring is the apex, and the myocardial rings of other frames are the multiple frame myocardial rings in the multiple frame myocardial rings except the target frame myocardial ring.

[0039] A third aspect of the present application provides a computer program product comprising computer-readable instructions, which, when executed on an electronic device, enables the electronic device to implement the method for generating a bull's eye diagram according to the first aspect or any implementation of the first aspect.

[0040] A fourth aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0041] The memory is used to store computer programs;

[0042] The processor is used to execute the computer program so that the electronic device can implement the method for generating a bull's eye image of the first aspect or any implementation of the first aspect.

[0043] In a fifth aspect, the present application provides a computer storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can generate the bull's eye diagram according to the first aspect or any implementation of the first aspect.

[0044] By means of the above technical scheme, the present application provides a method for generating a bull's eye image and a related device, the method comprising determining a multi-frame horizontal long-axis image, a multi-frame vertical long-axis image and a multi-frame short-axis image of the myocardium in a cardiac axis coordinate system; identifying the images to obtain a multi-frame ellipse center, an ellipse major axis radius of the multi-frame horizontal long-axis image, an ellipse major axis radius of the multi-frame vertical long-axis image and a circular radius of the multi-frame short-axis image; determining a target frame interval in the short-axis direction based on the identified information; determining a multi-frame ring and a multi-frame myocardial area based on the acquired frame number of the target frame interval and the short-axis image corresponding to the target frame interval, and scaling the multi-frame myocardial area to the corresponding frame rings to obtain a multi-frame myocardial ring; determining a target frame myocardial ring, projecting other frame myocardial rings onto the target frame myocardial ring, and converting the image obtained after projection to polar coordinates to obtain a bull's eye image of the myocardium, wherein the center of the outer circle corresponding to the target frame myocardial ring is the apex, and the other frame myocardial rings are the multi-frame myocardial rings in the multi-frame myocardial ring except the target frame myocardial ring. The bull's-eye map is quickly generated by accurately analyzing and processing tomographic images of specific frames, which reduces the dependence on a large number of samples and improves the efficiency of bull's-eye map generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the originals and elements are not necessarily drawn to scale.

[0046] Figure 1 A schematic diagram of a process for generating a bull's-eye image provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of the horizontal long axis, vertical long axis, and short axis of the myocardium provided in an embodiment of the present application;

[0048] Figure 3 A schematic diagram of a short-axis image corresponding to a target frame provided in an embodiment of the present application;

[0049] Figure 4 A schematic diagram of a ring provided in an embodiment of the present application;

[0050] Figure 5 A schematic diagram of a myocardial ring provided in an embodiment of the present application;

[0051] Figure 6 A schematic diagram of an image obtained after projection provided in an embodiment of the present application;

[0052] Figure 7 A schematic diagram of a myocardial bull's-eye diagram provided in an embodiment of the present application;

[0053] Figure 8 A schematic diagram of a color bull's-eye image of the myocardium provided in an embodiment of the present application;

[0054] Figure 9 A schematic structural diagram of a device for generating a bull's-eye image provided in an embodiment of the present application;

[0055] Figure 10 A schematic diagram of the hardware structure of a device for generating a bull's-eye image provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] The following describes the embodiments of the present application in conjunction with the accompanying drawings. The terms used in the implementation methods of the present application are only used to explain the specific embodiments of the present application and are not intended to limit the present application.

[0057] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0058] The terms "first", "second", etc. in the specification and claims 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 terms used in this way can be interchangeable under appropriate circumstances, and this is merely a way of distinguishing the objects of the same attributes when describing them in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0059] In order to reduce the dependence on a large number of samples and improve the efficiency of generating a bull's-eye diagram, the present application provides a method for generating a bull's-eye diagram. The method for generating a bull's-eye diagram provided by the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0060] Please see the attached Figure 1 , Figure 1 This is a flow chart of a method for generating a bull's eye image provided in an embodiment of the present application. The method may include the following steps:

[0061] Step S101: determining a tomographic image of the myocardium in the cardiac axis coordinate system, wherein the tomographic image of the myocardium in the cardiac axis coordinate system includes multiple frames of horizontal long axis images, multiple frames of vertical long axis images, and multiple frames of short axis images.

[0062] In this application, a tomographic image of the myocardium is first acquired in a human coordinate system. The coordinate system of the tomographic image of the myocardium in the human coordinate system is then rotated to obtain a rotated tomographic image. Finally, bilinear interpolation is performed on the rotated tomographic image to obtain a tomographic image of the myocardium in a cardiac axis coordinate system.

[0063] Myocardial tomographic images are typically acquired in the human body's coordinate system. However, due to factors such as body posture and the position of the scanning device, directly acquired myocardial tomographic images are not conducive to subsequent analysis and processing. Therefore, tomographic images of the myocardium acquired in the human body coordinate system are converted to tomographic images in the cardiac axis coordinate system. The cardiac axis coordinate system is centered on the heart and is more consistent with cardiac morphology and function, facilitating more accurate analysis of myocardial morphology and function.

[0064] A tomography device can be used to scan a human body, obtain a tomography image of the myocardium in a human coordinate system, calculate a rotation matrix from the human coordinate system to the cardiac axis coordinate system, and apply the rotation matrix to rotate the tomography image of the myocardium in the human coordinate system to obtain a rotated tomography image. It should be noted that the tomography device can be a single photon emission computed tomography device, a positron emission tomography device, or the like.

[0065] Specifically, the Euler angles are required to determine the rotation matrix from the conventional coordinate system to the central axis coordinate system. The Euler angles include the precession angle ψ, the nutation angle θ, and the rotation angle φ. Set the original position of the central axis coordinate system Ox′y′z′ to coincide with the conventional coordinate system Oxyz. First, rotate the precession angle ψ around the Oz axis, which can be expressed as the rotation matrix Z(ψ); then rotate the nutation angle θ around the N axis obtained by the previous rotation, which can be expressed as the rotation matrix N(θ); finally, rotate the rotation angle φ around the Oz' axis, which can be expressed as the rotation matrix Z'(φ). Based on the rotation matrix Z(ψ), the rotation matrix N(θ), and the rotation matrix Z'(φ), determine the rotation matrix R(ψ, θ, φ), where Z, N, Z', and R are rotation operators. For details, please refer to the following formula:

[0066]

[0067] Since rotation may cause changes in the pixel positions of an image, resulting in pixel misalignment or missing pixels, bilinear interpolation is a commonly used image interpolation method used to fill these missing pixel positions and maintain the smoothness of the image.

[0068] The rotated tomographic image can be scanned to identify locations where pixels are misplaced or missing. A bilinear interpolation algorithm is then used to calculate and fill the pixel values ​​of these missing locations based on the values ​​of the surrounding pixels. The above steps are repeated until all missing locations are filled, thereby obtaining the final tomographic image of the myocardium in the cardiac axis coordinate system.

[0069] The myocardial tomography images in the cardiac axis coordinate system usually obtain multiple frames of images at different angles to comprehensively evaluate the structure and function of the heart. These images include multiple horizontal long axis images, multiple vertical long axis images, and multiple short axis images. Figure 2 , Figure 2 This is a schematic diagram of the horizontal long axis, vertical long axis and short axis of the myocardium provided in an embodiment of the present application.

[0070] Step S102: Identify the multi-frame horizontal long axis images, the multi-frame vertical long axis images and the multi-frame short axis images to obtain the multi-frame ellipse center, the ellipse long axis radius of the multi-frame horizontal long axis images, the ellipse long axis radius of the multi-frame vertical long axis images and the circle radius of the multi-frame short axis images.

[0071] In this application, since the shape of the myocardium will be different in tomographic images in different directions, it is necessary to identify each frame of the image separately to obtain key features in multiple frames of horizontal long-axis images, multiple frames of vertical long-axis images, and multiple frames of short-axis images.

[0072] To accurately extract these features from each frame, an ellipse detection algorithm can be used. Typically, an ellipse detection algorithm performs edge detection on an image, extracting edge information from the image. It then uses the geometric properties of an ellipse (e.g., the tangent line at any point on the ellipse is perpendicular to the two radii passing through the ellipse's center at that point) to identify the ellipse's shape, as well as key parameters such as the ellipse's center, major axis radius, and minor axis radius.

[0073] It should be noted that ellipse detection is an image processing technique that can accurately identify elliptical objects in complex image backgrounds. Advanced ellipse detection algorithms include randomized Hough transform algorithms and edge-based ellipse fitting algorithms.

[0074] In addition, the accuracy of ellipse detection can be further improved by improving the image quality through preprocessing steps, such as image denoising, contrast enhancement, and USM (Unsharp Mask Sharpening).

[0075] Step S103: determining a target frame interval in the short axis direction based on the ellipse major axis radius of the multi-frame horizontal long axis image, the ellipse major axis radius of the multi-frame vertical long axis image, the circular radius of the multi-frame short axis image and the multi-frame ellipse center.

[0076] In the present application, the pixel size of the multi-frame horizontal long axis image, the pixel size of the multi-frame vertical long axis image and the inter-layer spacing of the multi-frame short axis image are first obtained. Then, based on the inter-layer spacing of the multi-frame short axis image, the pixel size of the multi-frame horizontal long axis image and the major axis radius of the ellipse of the multi-frame horizontal long axis image, the first frame interval in the short axis direction is calculated. Then, based on the inter-layer spacing of the multi-frame short axis image, the pixel size of the multi-frame vertical long axis image and the major axis radius of the ellipse of the multi-frame vertical long axis image, the second frame interval in the short axis direction is calculated. Then, the frame interval with the larger range in the first frame interval in the short axis direction and the second frame interval in the short axis direction is used as the candidate frame interval in the short axis direction. Finally, based on the circular radius of the multi-frame short axis image and the center of the multi-frame ellipse, the target frame interval in the short axis direction is determined from the candidate frame intervals in the short axis direction.

[0077] It should be noted that the pixel size of a horizontal long-axis image refers to the number of pixels in the image in the horizontal and vertical directions; the pixel size of a multi-frame vertical long-axis image refers to the number of pixels in the vertical long-axis image in the horizontal and vertical directions. The interslice spacing of a multi-frame short-axis image refers to the physical distance between two adjacent short-axis images.

[0078] Specifically, the pixel size of multiple horizontal long-axis images can be used to convert the major axis radius of the ellipse in the horizontal long-axis image into an actual physical size. The inter-slice spacing of multiple short-axis images and the converted physical size can be used to estimate the approximate position of the myocardium in the short-axis direction, thereby obtaining a range of the number of frames in the short-axis direction. This range constitutes the first frame interval. The pixel size of multiple vertical long-axis images can be used to convert the major axis radius of the ellipse in the vertical long-axis image into an actual physical size. The inter-slice spacing of multiple short-axis images and the converted physical size can be used to estimate the approximate position of the myocardium in the short-axis direction, thereby obtaining a range of the number of frames in the short-axis direction. This range constitutes the second frame interval.

[0079] In order to more likely include the complete myocardial region, the larger one between the first frame interval and the second frame interval is used as the candidate frame interval in the short-axis direction.

[0080] First, the starting frame in the short-axis direction is selected from the candidate frame intervals along the short axis. The vertex of the circular radius of the short-axis image corresponding to the starting frame in the short axis direction is the cardiac apex. Then, the ending frame in the short axis direction is selected from the candidate frame intervals along the short axis direction. The center of the ellipse corresponding to the ending frame in the short axis direction is the cardiac base. Finally, based on the starting and ending frames in the short axis direction, the target frame interval in the short axis direction is determined.

[0081] In each short-axis image frame within the candidate frame interval, observe and measure the major axis radius and center of the ellipse. The apex is a key anatomical feature of the myocardium and typically appears as the vertex of the major axis radius of the ellipse in the short-axis image. Therefore, the frame with the vertex of the circular radius of the short-axis image at the apex can be used as the starting frame in the short-axis direction. The base of the heart is another key anatomical feature of the myocardium and typically appears as the center of the ellipse in the short-axis image. Therefore, the frame with the center of the ellipse at the base of the short-axis image can be used as the ending frame in the short-axis direction.

[0082] The target frame interval in the short axis direction is determined from the start frame to the end frame. The short axis image corresponding to the target frame interval includes the heart area from the apex to the base of the heart, which is the key area for subsequent image analysis or diagnosis. For ease of understanding, please refer to Figure 3 , Figure 3 A schematic diagram of a short-axis image corresponding to a target frame provided in an embodiment of the present application.

[0083] Step S104: Based on the acquired frame number of the target frame interval and the short-axis image corresponding to the target frame interval, determine the multi-frame rings and the multi-frame myocardial area, and scale the multi-frame myocardial area to the corresponding frame rings to obtain the multi-frame myocardial rings.

[0084] In this application, the short-axis image corresponding to the target frame interval is first detected to obtain the center and radius of the multi-frame outer circle. Then, based on the number of frames in the target frame interval and the maximum outer circle radius, the ring width of each frame in the target frame interval is calculated. Based on the ring width of each frame, the corresponding multi-frame outer circle center and multi-frame outer circle radius are combined to obtain a multi-frame ring, in which the center of the multi-frame outer circle of the multi-frame ring coincides. Finally, the short-axis image corresponding to the target frame interval is divided to obtain the multi-frame myocardial region.

[0085] Specifically, the Hough transform circle detection algorithm can be used to detect each short-axis image frame in the target frame interval, find the outer boundary circle of the myocardial tissue in each frame, and extract the outer circle center and outer circle radius. It should be noted that the Hough transform circle detection algorithm is an image processing technology that can automatically detect circular structures in images.

[0086] By comparing all outer circle radii, we can find the outer circle with the largest radius and its corresponding outer circle center. Divide the largest outer circle radius by the number of frames in the target frame interval to calculate the ring width for each frame, ensuring that each frame has a uniform or regularly varying ring width.

[0087] For each frame, a ring is drawn with the center of the outer circle as the center and the outer diameter as the outer boundary (the inner diameter can also be calculated considering the ring width). Each frame image corresponds to a ring. The centers of these rings coincide, indicating that they are all at the same myocardial center position, but the radius varies from frame to frame. For easier understanding, please refer to Figure 4 , Figure 4 A schematic diagram of a ring provided in an embodiment of the present application.

[0088] The watershed segmentation algorithm can be used to accurately segment myocardial tissue from surrounding structures in each short-axis image frame corresponding to the target frame interval, thereby obtaining the myocardial region in each short-axis image frame. It should be noted that the watershed segmentation algorithm is a segmentation method based on image topology and is typically used for grayscale or binary images. In myocardial segmentation, this algorithm can identify the boundary between myocardial tissue and surrounding tissue, thereby achieving accurate segmentation.

[0089] The scaled size of the myocardial region can be determined based on the multi-frame rings. Then, the bilinear interpolation method is used to scale each frame of the myocardial region to the scaled size. Finally, the multi-frame myocardial ring is obtained by adding it to the corresponding position in the filled rings of each frame. The multi-frame myocardial ring not only contains the information of the myocardial region, but also is associated with the overall structure of the myocardium through the ring. For easier understanding, please refer to Figure 5 , Figure 5 This is a schematic diagram of a myocardial ring provided in an embodiment of the present application. It should be noted that bilinear interpolation is a commonly used image scaling method that can achieve a smooth scaling effect while maintaining image details.

[0090] Step S105: Determine the target frame myocardial ring, project the myocardial rings of other frames onto the target frame myocardial ring, and convert the projected image into polar coordinates to obtain a bull's eye image of the myocardium. The center of the outer circle corresponding to the target frame myocardial ring is the apex of the heart, and the myocardial rings of other frames are the multiple frames of myocardial rings except the target frame myocardial ring.

[0091] In this application, among the multiple frames of myocardial annulus, a frame with the outer circle of the myocardial annulus as the apex is selected as the target frame. The myocardial annulus of this frame is used as a reference, and the myocardial annulus of all other frames except the target frame is projected onto the plane where the myocardial annulus of the target frame is located. During the projection process, it is ensured that the radial areas corresponding to each layer do not overlap with each other to maintain the clarity and accuracy of the myocardial structure. For ease of understanding, please refer to Figure 6 , Figure 6 A schematic diagram of an image obtained after projection provided in an embodiment of the present application.

[0092] The projected image is converted into a polar coordinate system (r, θ). In the polar coordinate system, r represents the radial distance (from the apex to the edge of the myocardium), and θ represents the central angle (the angle around the apex). In the polar coordinate system, the myocardial rings of each frame are superimposed together to form a bull's-eye image of the myocardium. The bull's-eye image of the myocardium shows the myocardial structure from the apex to the bottom of the heart, and each layer of myocardial area is clearly distinguishable in the radial and circumferential directions. The bull's-eye image of the myocardium is divided into multiple rings in the order from the apex to the bottom of the heart, and each ring is further divided into 1, 4, 6, and 6 segments according to the central angle, for a total of 17 segments, which helps to conduct a more detailed analysis and evaluation of the myocardium. For ease of understanding, please refer to Figure 7 , Figure 7 This is a schematic diagram of a myocardial bull's-eye image provided in an embodiment of the present application. The image data type being processed is ushort, so 65535 can be used as the maximum value. The pixel mean of each partition is divided by this maximum value, and the resulting percentage is multiplied by 100 to obtain the score for that partition.

[0093] In summary, the present application provides a method for generating a bull's eye image, which includes determining multiple horizontal long-axis images, multiple vertical long-axis images, and multiple short-axis images of the myocardium in a cardiac axis coordinate system; identifying the images to obtain the center of a multi-frame ellipse, the major axis radius of the ellipse of the multi-frame horizontal long-axis images, the major axis radius of the ellipse of the multi-frame vertical long-axis images, and the circular radius of the multi-frame short-axis images; determining the target frame interval in the short-axis direction based on the identified information; determining the multi-frame ring and the multi-frame myocardial area based on the number of frames of the acquired target frame interval and the short-axis image corresponding to the target frame interval, and projecting the myocardial rings of other frames onto the myocardial ring of the target frame, and converting the image obtained after the projection into polar coordinates to obtain a bull's eye image of the myocardium, the center of the outer circle corresponding to the target frame myocardial ring is the apex, and the myocardial rings of other frames are the multi-frame myocardial rings except the target frame myocardial ring in the multi-frame myocardial rings, the center of the outer circle corresponding to the target frame myocardial ring is the apex, and the myocardial rings of other frames are the multi-frame myocardial rings except the target frame myocardial ring in the multi-frame myocardial rings. The bull's-eye map is quickly generated by accurately analyzing and processing tomographic images of specific frames, which reduces the dependence on a large number of samples and improves the efficiency of bull's-eye map generation.

[0094] Furthermore, based on the above embodiment, the method may further include calculating the standardized uptake value of each segment and the average standardized uptake value of the bull's-eye chart. For each segment, the percentage of the standardized uptake value of the segment to the average standardized uptake value of the bull's-eye chart is calculated, and the percentage is used as the score of the segment.

[0095] It's important to note that the standardized uptake value (SUR) is a commonly used quantitative metric in medical imaging to assess the extent of tissue uptake of radiotracers. Calculation of the SUR typically involves dividing the average pixel value within a segment by a reference value (such as injected dose or body weight).

[0096] In this application, the standardized uptake value (SUR) for each segment is calculated based on the pixel values ​​within each segment, along with the average SUR of all segments in the bull's-eye plot (the average SUR). For each segment, the percentage of its SUR relative to the average SUR is calculated, and this percentage serves as the segment score to assess the myocardial uptake capacity or functional status of that segment. By calculating the percentage score, each segment's level relative to the bull's-eye plot can be quantitatively assessed, making the assessment more objective and accurate.

[0097] The score of each segment can also be mapped to RGB space for color coding. Different colors represent different score ranges, thus generating a color bull's-eye diagram partition unit. The color bull's-eye diagram provides an intuitive visual representation, which facilitates the rapid identification of abnormal areas of myocardial function. For easier understanding, please refer to Figure 8 , Figure 8 This is a schematic diagram of a color bull's-eye image of the myocardium provided in an embodiment of the present application.

[0098] The above describes a method for generating a bull's-eye image provided in an embodiment of the present application. The following describes an apparatus for executing the above method for generating a bull's-eye image.

[0099] See also Figure 9 , Figure 9 This is a schematic diagram of the structure of a device for generating a bull's eye image provided in an embodiment of the present application. Figure 3 As shown, the device for generating the bull's-eye diagram includes:

[0100] The first determining unit 11 is used to determine a tomographic image of the myocardium in the cardiac axis coordinate system, wherein the tomographic image of the myocardium in the cardiac axis coordinate system includes multiple frames of horizontal long axis images, multiple frames of vertical long axis images, and multiple frames of short axis images.

[0101] The identification unit 12 is used to identify the multi-frame horizontal long-axis images, the multi-frame vertical long-axis images and the multi-frame short-axis images to obtain the multi-frame ellipse center, the ellipse long-axis radius of the multi-frame horizontal long-axis images, the ellipse long-axis radius of the multi-frame vertical long-axis images and the circular radius of the multi-frame short-axis images.

[0102] The second determination unit 13 is used to determine the target frame interval in the short axis direction based on the ellipse major axis radius of the multiple frames of horizontal long axis images, the ellipse major axis radius of the multiple frames of vertical long axis images, the circular radius of the multiple frames of short axis images and the center of the multiple frames of ellipse.

[0103] The third determination unit 14 is used to determine the multi-frame rings and multi-frame myocardial areas based on the acquired frame number of the target frame interval and the short-axis image corresponding to the target frame interval, and scale the multi-frame myocardial areas to the corresponding rings of each frame to obtain multi-frame myocardial rings.

[0104] The fourth determination unit 15 is used to determine the target frame myocardial ring, and project the other frame myocardial rings onto the target frame myocardial ring, and convert the image obtained after projection into polar coordinates to obtain a bull's eye image of the myocardium, where the center of the outer circle corresponding to the target frame myocardial ring is the apex, and the other frame myocardial rings are the multiple frame myocardial rings in the multiple frame myocardial rings except the target frame myocardial ring.

[0105] In a possible implementation, the first determining unit 11 includes:

[0106] The first acquisition subunit is used to acquire a tomographic image of the myocardium in a human body coordinate system.

[0107] The rotation subunit is used to perform coordinate system rotation on the tomographic image of the myocardium in the human body coordinate system to obtain a rotated tomographic image.

[0108] The interpolation subunit is used to perform bilinear interpolation on the rotated tomographic image to obtain a tomographic image of the myocardium in a cardiac axis coordinate system.

[0109] In a possible implementation, the second determining unit 13 includes:

[0110] The second acquisition subunit is configured to acquire the pixel size of the multiple frames of horizontal long-axis images, the pixel size of the multiple frames of vertical long-axis images, and the inter-slice spacing of the multiple frames of short-axis images.

[0111] The first calculation subunit is used to calculate the first frame interval in the short axis direction based on the layer spacing of the multiple frames of short axis images, the pixel size of the multiple frames of horizontal long axis images and the ellipse major axis radius of the multiple frames of horizontal long axis images.

[0112] The second calculation subunit is used to calculate the second frame interval in the short axis direction based on the layer spacing of the multiple frames of short axis images, the pixel size of the multiple frames of vertical long axis images and the ellipse major axis radius of the multiple frames of vertical long axis images.

[0113] The first determining subunit is configured to select a frame interval with a larger range between the first frame interval in the short-axis direction and the second frame interval in the short-axis direction as a candidate frame interval in the short-axis direction.

[0114] The second determining subunit is configured to determine a target frame interval in the short axis direction from candidate frame intervals in the short axis direction based on the circular radius of the multi-frame short axis images and the center of the multi-frame ellipse.

[0115] In a possible implementation, the second determining subunit includes:

[0116] The first screening subunit is configured to screen out a starting frame in the short-axis direction from the candidate frame interval in the short-axis direction, wherein the vertex of the circular radius of the short-axis image corresponding to the starting frame in the short-axis direction is the apex of the heart.

[0117] The second screening sub-unit is configured to screen out an end frame in the short axis direction from the candidate frame interval in the short axis direction, wherein the ellipse center corresponding to the end frame in the short axis direction is the heart base.

[0118] The third determining subunit is configured to determine a target frame interval in the short-axis direction based on a start frame in the short-axis direction and an end frame in the short-axis direction.

[0119] In a possible implementation, the third determining unit 14 for determining the multi-frame rings and the multi-frame myocardial regions based on the acquired number of frames of the target frame interval and the short-axis image corresponding to the target frame interval includes:

[0120] The detection subunit is used to detect the short-axis image corresponding to the target frame interval to obtain the center and radius of the outer circle of multiple frames.

[0121] The combining subunit is used to calculate the ring width of each frame in the target frame interval based on the number of frames in the target frame interval and the maximum outer circle radius, and based on the ring width of each frame, combine the corresponding centers of the multi-frame outer circles and the multi-frame outer circle radii to obtain the multi-frame circular ring, and the centers of the multi-frame outer circles of the multi-frame circular ring coincide with each other.

[0122] The division subunit is used to divide the short-axis image corresponding to the target frame interval to obtain the multi-frame myocardial area.

[0123] In a possible implementation, the myocardial bull's-eye image includes multiple segments, and the device further includes:

[0124] A calculation unit is used to calculate the standardized uptake value of each of the segments and the average standardized uptake value of the bull's eye image.

[0125] A fifth determination unit is configured to calculate, for each segment, a percentage of the standardized uptake value of the segment to the average standardized uptake value of the bull's-eye image, and use the percentage as a score of the segment.

[0126] An electronic device is also provided in an embodiment of the present application. Figure 10 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 10 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0127] like Figure 10 As shown, the electronic device may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 1001, which can perform various appropriate actions and processes based on programs stored in a read-only memory (ROM) 1002 or programs loaded from a storage device 1008 into a random access memory (RAM) 1003. When the electronic device is powered on, the RAM 1003 also stores various programs and data required for the operation of the electronic device. The processing device 1001, ROM 1002, and RAM 1003 are interconnected via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0128] Typically, the following devices may be connected to the I / O interface 1005: an input device 1006 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 1007 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 1008 including, for example, a memory card, a hard disk, etc.; and a communication device 1009. The communication device 1009 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Figure 10 The electronic device is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0129] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any method for generating a bull's eye image provided in the embodiment of the present application.

[0130] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any method for generating a bull's eye image provided in an embodiment of the present application.

[0131] It should also be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided in this application, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines.

[0132] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course can also be implemented by special hardware including application-specific integrated circuits, special CPUs, special memories, special components, etc. In general, all functions performed by computer programs can be easily implemented with corresponding hardware, and the specific hardware structures used to implement the same function can also be diverse, such as analog circuits, digital circuits or special circuits, etc. However, for the present application, software program implementation is a better implementation method in most cases. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer's floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk or optical disk, etc., and includes a number of instructions to enable a computer device (which can be a personal computer, training equipment, or network equipment, etc.) to execute the methods described in each embodiment of the present application.

[0133] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0134] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, a computer, a training device or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website, a computer, a training device or a data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

Claims

1. A method for generating a bull's eye graph, characterized in that: include: Determining a tomographic image of the myocardium in a cardiac axis coordinate system, wherein the tomographic image of the myocardium in the cardiac axis coordinate system includes multiple frames of horizontal long axis images, multiple frames of vertical long axis images, and multiple frames of short axis images; Identifying the multiple frames of horizontal long-axis images, the multiple frames of vertical long-axis images, and the multiple frames of short-axis images to obtain a multi-frame ellipse center, an ellipse long-axis radius of the multiple frames of horizontal long-axis images, an ellipse long-axis radius of the multiple frames of vertical long-axis images, and a circular radius of the multiple frames of short-axis images; determining a target frame interval in the short axis direction based on the ellipse major axis radius of the multiple frames of horizontal long axis images, the ellipse major axis radius of the multiple frames of vertical long axis images, the circular radius of the multiple frames of short axis images, and the center of the multiple frames of ellipse; Determining a multi-frame annulus and a multi-frame myocardial region based on the acquired number of frames of the target frame interval and the short-axis image corresponding to the target frame interval, and scaling the multi-frame myocardial region to the corresponding annulus of each frame to obtain a multi-frame myocardial annulus; Determine a target frame myocardial ring, project other frame myocardial rings onto the target frame myocardial ring, and convert the projected image into polar coordinates to obtain a bull's eye image of the myocardium, wherein the center of the outer circle corresponding to the target frame myocardial ring is the apex of the heart, and the other frame myocardial rings are multiple frame myocardial rings in the multiple frame myocardial rings excluding the target frame myocardial ring; The determining of the target frame interval in the short axis direction based on the ellipse major axis radius of the multiple frames of horizontal long axis images, the ellipse major axis radius of the multiple frames of vertical long axis images, the circular radius of the multiple frames of short axis images, and the center of the multiple frames of ellipse includes: Acquiring the pixel size of the multiple frames of horizontal long-axis images, the pixel size of the multiple frames of vertical long-axis images, and the inter-slice spacing of the multiple frames of short-axis images; Calculating a first frame interval in the short axis direction based on the inter-slice spacing of the multiple-frame short axis images, the pixel size of the multiple-frame horizontal long axis images, and the ellipse major axis radius of the multiple-frame horizontal long axis images; Calculating a second frame interval in the short-axis direction based on the inter-slice spacing of the multiple-frame short-axis images, the pixel size of the multiple-frame vertical long-axis images, and the ellipse major axis radius of the multiple-frame vertical long-axis images; selecting a larger frame interval between the first frame interval in the short-axis direction and the second frame interval in the short-axis direction as a candidate frame interval in the short-axis direction; Based on the circular radius of the multi-frame short-axis images and the center of the multi-frame ellipse, a target frame section in the short-axis direction is determined from the candidate frame sections in the short-axis direction.

2. The method for generating a bull's eye diagram according to claim 1, wherein: Determining a tomographic image of the myocardium in a cardiac axis coordinate system includes: Acquire a tomographic image of the myocardium in a human coordinate system; performing coordinate rotation on the tomographic image of the myocardium in the human body coordinate system to obtain a rotated tomographic image; Bilinear interpolation is performed on the rotated tomographic image to obtain a tomographic image of the myocardium in a cardiac axis coordinate system.

3. The method for generating a bull's eye diagram according to claim 1, wherein: The determining, based on the circular radius of the multi-frame short-axis images and the center of the multi-frame ellipse, a target frame interval in the short-axis direction from the candidate frame intervals in the short-axis direction, comprises: Filtering a starting frame in the short-axis direction from the candidate frame interval in the short-axis direction, wherein the vertex of the circular radius of the short-axis image corresponding to the starting frame in the short-axis direction is the apex of the heart; Filtering out an end frame in the short-axis direction from the candidate frame intervals in the short-axis direction, wherein the center of the ellipse corresponding to the end frame in the short-axis direction is the heart base; A target frame section in the short-axis direction is determined based on the start frame in the short-axis direction and the end frame in the short-axis direction.

4. The method for generating a bull's eye diagram according to claim 3, wherein: The determining of the multi-frame annulus and the multi-frame myocardial region based on the acquired number of frames of the target frame interval and the short-axis image corresponding to the target frame interval includes: Detecting the short-axis image corresponding to the target frame interval to obtain the center and radius of the outer circle of multiple frames; Based on the obtained number of frames in the target frame interval and the maximum outer circle radius, a ring width of each frame in the target frame interval is calculated, and based on the ring width of each frame, the corresponding centers of the outer circles of multiple frames and the outer circle radii of the multiple frames are combined to obtain the multi-frame circular ring, wherein the centers of the outer circles of multiple frames of the multi-frame circular ring coincide with each other; The short-axis image corresponding to the target frame interval is divided to obtain the multi-frame myocardial region.

5. The method for generating a bull's eye diagram according to claim 4, wherein: The bull's-eye image of the myocardium includes a plurality of segments, and the method further includes: calculating a standardized uptake value of each of the segments and an average standardized uptake value of the bull's-eye image; For each segment, the percentage of the standardized uptake value of the segment to the average standardized uptake value of the bull's-eye image was calculated, and the percentage was used as the score of the segment.

6. A device for generating a bull's eye diagram, characterized in that: include: A first determining unit is configured to determine a tomographic image of the myocardium in a cardiac axis coordinate system, wherein the tomographic image of the myocardium in the cardiac axis coordinate system includes multiple frames of horizontal long axis images, multiple frames of vertical long axis images, and multiple frames of short axis images; an identification unit, configured to identify the multi-frame horizontal long-axis images, the multi-frame vertical long-axis images, and the multi-frame short-axis images, and obtain a multi-frame ellipse center, an ellipse long-axis radius of the multi-frame horizontal long-axis images, an ellipse long-axis radius of the multi-frame vertical long-axis images, and a circular radius of the multi-frame short-axis images; a second determining unit, configured to determine a target frame interval in a minor axis direction based on the ellipse major axis radius of the multiple frames of horizontal major axis images, the ellipse major axis radius of the multiple frames of vertical major axis images, the circular radius of the multiple frames of minor axis images, and the center of the multiple frames of ellipse; a third determining unit, configured to determine a multi-frame annulus and a multi-frame myocardial region based on the number of frames acquired in the target frame interval and the short-axis image corresponding to the target frame interval, and scale the multi-frame myocardial region onto the corresponding annulus of each frame to obtain a multi-frame myocardial annulus; a fourth determining unit, configured to determine a target frame myocardial ring, project the myocardial rings of other frames onto the target frame myocardial ring, and convert the projected image into polar coordinates to obtain a bull's-eye image of the myocardium, wherein the center of the outer circle corresponding to the target frame myocardial ring is the apex of the heart, and the myocardial rings of other frames are the multiple myocardial rings of the multiple frames excluding the target frame myocardial ring; The second determining unit includes: a second acquisition subunit, configured to acquire the pixel size of the multiple frames of horizontal long-axis images, the pixel size of the multiple frames of vertical long-axis images, and the inter-slice spacing of the multiple frames of short-axis images; A first calculation subunit is configured to calculate a first frame interval in the short axis direction based on the inter-slice spacing of the multiple frames of short axis images, the pixel size of the multiple frames of horizontal long axis images, and the radius of the ellipse major axis of the multiple frames of horizontal long axis images; A second calculation subunit is configured to calculate a second frame interval in the short axis direction based on the inter-slice spacing of the multiple frames of short axis images, the pixel size of the multiple frames of vertical long axis images, and the radius of the ellipse major axis of the multiple frames of vertical long axis images; a first determining subunit, configured to select a frame interval having a larger range between the first frame interval in the short-axis direction and the second frame interval in the short-axis direction as a candidate frame interval in the short-axis direction; The second determining subunit is configured to determine a target frame interval in the short axis direction from candidate frame intervals in the short axis direction based on the circular radius of the multi-frame short axis images and the center of the multi-frame ellipse.

7. A computer program product, characterized in that The method comprises computer-readable instructions, which, when executed on an electronic device, enable the electronic device to implement the method for generating a bull's eye diagram according to any one of claims 1 to 5.

8. An electronic device, characterized in that: comprising at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is configured to execute the computer program so that the electronic device can implement the method for generating a bull's eye image according to any one of claims 1 to 5.

9. A computer storage medium, characterized in that The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the method for generating a bull's eye diagram as described in any one of claims 1 to 5.

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