Medical image processing method, device, computer equipment and storage medium

Abstract

The present application discloses a medical image processing method, apparatus, computer device, and storage medium. The medical image processing method includes: obtaining contour data and a contour reference range of a target object, calculating a normal vector on the contour data and adjusting it to a uniform orientation to obtain adjusted contour data; performing internal interpolation on the adjusted contour data to obtain interpolated contour data; and reconstructing the interpolated contour data to obtain a closed reconstructed medical image. In the embodiment of the present application, by filling in and interpolating the interior of a contour composed of contour data, sufficient information is added to the upper and lower contour layers, so that these inserted points are reconstructed as plane information during the reconstruction process, and an accurate closed manifold surface without pseudo-surfaces or holes can be obtained.

Description

Technical Field

[0001] The present application relates to medical technicians and fields, and in particular to a medical image processing method, apparatus, computer equipment and storage medium. Background Art

[0002] In order to better obtain information about the lesion site in a patient's body in modern medicine, three-dimensional imaging technology is usually used according to target information of a specific target site, for example, a three-dimensional CT image is constructed based on the target information.

[0003] When outlining objects (such as the brain or lungs) across multiple slices in a computed tomography (CT) image, if some of the outlined objects are not closed in the reconstructed space but have large openings, the resulting 3D reconstructed contour surface will contain redundant surfaces, also known as pseudo-surfaces, at its edges. These redundant surfaces remain in the reconstructed image, hindering the acquisition of useful information.

[0004] Specifically, for medical contouring images, such as the images of the objects (such as the brain, lungs, etc.) in multiple slices of a CT image, it is composed of layers of closed contour points. In the first and last layers, because there is no redundant point information, an open shape is formed. If the opening is large, then the contour surface after Poisson reconstruction will contain redundant surfaces at its edges, that is, pseudo surfaces. Even for some smaller openings, there is no redundant information, which causes the reconstruction algorithm to interpolate redundant values, resulting in the reconstructed surface exceeding the original contour range. Figure 1 As shown, Figure 1 To reconstruct the brain contour, the line composed of black dots is the outlined contour points. After Poisson reconstruction, redundant surfaces (i.e., pseudo-surfaces) appear outside the contour, such as the gray surface that does not contain the contour line.

[0005] How to eliminate the pseudo-surfaces in the image after Poisson reconstruction, which is caused by the large opening holes in the top and bottom layers of the medical image outline reconstruction data, is a technical problem to be solved in this application. The current methods include limiting the generation of pseudo-surfaces through envelope constraints during Poisson reconstruction, cutting out pseudo-surfaces through medical-specific slicing restrictions, and improving the method of simultaneously cutting out pseudo-surfaces and points and rearranging the point sequence and the triangle indexes that make up the surface. For the cutting method, although the pseudo-surfaces are cut out, some irregular holes are left, destroying the original topological structure, and non-manifold or isolated surfaces may appear, which brings difficulties to the subsequent surface operations on the surface model. Summary of the Invention

[0006] The embodiments of the present application provide a medical image processing method, apparatus, computer equipment, and storage medium. By filling in interpolation inside a contour composed of contour data, sufficient information is added to the upper and lower contour layers, so that these inserted points are reconstructed as plane information during the reconstruction process, and an accurate closed manifold surface without pseudo-surfaces and holes can be obtained.

[0007] In one aspect, the present application provides a method for processing medical images, the method comprising:

[0008] Obtaining the contour data and contour reference range of the target object;

[0009] Calculating the normal vector of the contour data and adjusting it to a uniform orientation to obtain adjusted contour data;

[0010] Performing internal interpolation on the adjusted contour data to obtain interpolated contour data;

[0011] The interpolated contour data is reconstructed to obtain a closed reconstructed medical image.

[0012] In some embodiments of the present application, the contour reference range of the target object includes multi-layer slice images of the target object, wherein each layer of the slice image contains contour data of the target object in a preset rectangular coordinate system, and the contour data of the target object in the preset rectangular coordinate system includes the coordinate values ​​of the target object in the X-axis, Y-axis and Z-axis directions in the preset rectangular coordinate system. The contour data of the same layer of slice images have the same coordinate value in the Z-axis direction and different coordinate values ​​in the X-axis and Y-axis directions.

[0013] In some embodiments of the present application, performing internal interpolation on the contour data to obtain interpolated contour data includes:

[0014] Performing internal interpolation on the contour data to obtain initial interpolated contour data;

[0015] Adjusting the normal vectors of the newly inserted contour point data in the initial interpolated contour data so that the normal vectors of the newly inserted contour points have a uniform orientation, thereby obtaining the interpolated contour data;

[0016] The normal vector of the contour point in the adjusted contour data has the same direction as the normal vector of the newly inserted contour point in the interpolated contour data.

[0017] In some embodiments of the present application, performing internal interpolation on the contour data to obtain initial interpolated contour data includes:

[0018] Extracting top-level contour data and bottom-level contour data from the contour data;

[0019] Determine a contour point data set to be interpolated based on the top contour data and the bottom contour data;

[0020] According to the contour point data set, internal interpolation is performed on the contour data to obtain initial interpolated contour data.

[0021] In some embodiments of the present application, determining the contour point data set to be interpolated based on the top contour data and the bottom contour data includes:

[0022] Determining an interpolation contour point set corresponding to target layer contour data, the target layer contour data including the top layer contour data and / or the bottom layer contour data, wherein the top layer contour data corresponds to a first interpolation contour point set, and the bottom layer contour data corresponds to a second interpolation contour point set;

[0023] A contour point data set to be interpolated is determined according to the first interpolation contour point set and the second interpolation contour point set.

[0024] In some embodiments of the present application, determining the interpolation contour point set corresponding to the target layer contour data includes:

[0025] Determine the center point of the contour of the target layer contour data;

[0026] If the contour center point is located inside the contour of the contour data, the contour center point is used as a contour point in the interpolation contour point set;

[0027] A contour point in the target layer contour data is respectively used as a target contour point, and a set of interpolated contour points corresponding to the target layer contour data is determined according to the target contour point and the contour center point.

[0028] In some embodiments of the present application, determining a set of interpolated contour points corresponding to the top contour data according to the target contour point and the contour center point includes:

[0029] Mapping the target contour point to a two-dimensional plane to remove the data in the Z-axis direction of the target contour point to obtain the plane coordinates of the target contour point;

[0030] Obtaining the plane coordinates of the center point of the contour;

[0031] The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point and the plane coordinates of the contour center point.

[0032] In some embodiments of the present application, determining the interpolation contour point to be interpolated according to the plane coordinates of the target contour point and the plane coordinates of the contour center point includes:

[0033] Connecting the target contour point with the contour center point to obtain a contour point connecting line;

[0034] Calculating the length of the contour point connecting line and the slope of the contour point connecting line;

[0035] The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connection line, and the slope of the contour point connection line.

[0036] In some embodiments of the present application, determining the current interpolation contour point to be interpolated based on the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connecting line, and the slope of the contour point connecting line includes:

[0037] Calculating the ordinate of the interpolated contour point according to the ordinate of the target contour point, the ordinate of the contour center point, and the length of the line connecting the contour points;

[0038] The abscissa of the interpolated contour point is calculated according to the abscissa of the target contour point, the abscissa of the contour center point, and the slope of the line connecting the contour points.

[0039] In some embodiments of the present application, the step of adjusting the normal vectors of the newly inserted contour point data in the initial interpolated contour data so that the normal vectors of the newly inserted contour points have a uniform orientation to obtain the interpolated contour data includes:

[0040] Determining the Z-axis direction component of the normal vector of the newly inserted contour point data according to the maximum value and the minimum value of the Z-axis direction component in the contour reference range, so that the normal vector of the newly inserted contour point has a uniform direction, thereby obtaining the interpolated contour data;

[0041] The normal vector of the contour point in the adjusted contour data has the same direction as the normal vector of the newly inserted contour point in the interpolated contour data.

[0042] In another aspect, the present application provides a medical image processing device, the medical image processing device comprising:

[0043] An acquisition module is used to obtain the contour data and contour reference range of the target object;

[0044] An adjustment module, configured to calculate a normal vector of the contour data and adjust the contour data to a uniform orientation to obtain adjusted contour data;

[0045] An interpolation module, configured to perform internal interpolation on the adjusted contour data to obtain interpolated contour data;

[0046] The reconstruction module is used to reconstruct the interpolated contour data to obtain a closed reconstructed medical image.

[0047] In some embodiments of the present application, the contour reference range of the target object includes multi-layer slice images of the target object, wherein each layer of the slice image contains contour data of the target object in a preset rectangular coordinate system, and the contour data of the target object in the preset rectangular coordinate system includes the coordinate values ​​of the target object in the X-axis, Y-axis and Z-axis directions in the preset rectangular coordinate system. The contour data of the same layer of slice images have the same coordinate value in the Z-axis direction and different coordinate values ​​in the X-axis and Y-axis directions.

[0048] In some implementations of the present application, the interpolation module is specifically used to:

[0049] Performing internal interpolation on the contour data to obtain initial interpolated contour data;

[0050] Adjusting the normal vectors of the newly inserted contour point data in the initial interpolated contour data so that the normal vectors of the newly inserted contour points have a uniform orientation, thereby obtaining the interpolated contour data;

[0051] The normal vector of the contour point in the adjusted contour data has the same direction as the normal vector of the newly inserted contour point in the interpolated contour data.

[0052] In some implementations of the present application, the interpolation module is specifically used to:

[0053] Extracting top-level contour data and bottom-level contour data from the contour data;

[0054] Determine a contour point data set to be interpolated based on the top contour data and the bottom contour data;

[0055] According to the contour point data set, internal interpolation is performed on the contour data to obtain initial interpolated contour data.

[0056] In some implementations of the present application, the interpolation module is specifically used to:

[0057] Determining an interpolation contour point set corresponding to target layer contour data, the target layer contour data including the top contour data and / or the bottom contour data, wherein the top contour data corresponds to a first interpolation contour point set, and the bottom contour data corresponds to a second interpolation contour point set;

[0058] A contour point data set to be interpolated is determined according to the first interpolation contour point set and the second interpolation contour point set.

[0059] In some implementations of the present application, the interpolation module is specifically used to:

[0060] Determine the center point of the contour of the target layer contour data;

[0061] If the contour center point is located inside the contour of the contour data, the contour center point is used as a contour point in the interpolation contour point set;

[0062] A contour point in the target layer contour data is respectively used as a target contour point, and a set of interpolated contour points corresponding to the target layer contour data is determined according to the target contour point and the contour center point.

[0063] In some implementations of the present application, the interpolation module is specifically used to:

[0064] Mapping the target contour point to a two-dimensional plane to remove the data in the Z-axis direction of the target contour point to obtain the plane coordinates of the target contour point;

[0065] Obtaining the plane coordinates of the center point of the contour;

[0066] The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point and the plane coordinates of the contour center point.

[0067] In some implementations of the present application, the interpolation module is specifically used to:

[0068] Connecting the target contour point with the contour center point to obtain a contour point connecting line;

[0069] Calculating the length of the contour point connecting line and the slope of the contour point connecting line;

[0070] The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connection line, and the slope of the contour point connection line.

[0071] In some implementations of the present application, the interpolation module is specifically used to:

[0072] Calculating the ordinate of the interpolated contour point according to the ordinate of the target contour point, the ordinate of the contour center point, and the length of the line connecting the contour points;

[0073] The abscissa of the interpolated contour point is calculated according to the abscissa of the target contour point, the abscissa of the contour center point, and the slope of the line connecting the contour points.

[0074] In some implementations of the present application, the interpolation module is specifically used to:

[0075] Determining the Z-axis direction component of the normal vector of the newly inserted contour point data according to the maximum value and the minimum value of the Z-axis direction component in the contour reference range, so that the normal vector of the newly inserted contour point has a uniform direction, thereby obtaining the interpolated contour data;

[0076] The normal vector of the contour point in the adjusted contour data has the same direction as the normal vector of the newly inserted contour point in the interpolated contour data.

[0077] On the other hand, the present application further provides a computer device, comprising:

[0078] one or more processors;

[0079] Memory; and

[0080] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the medical image processing method according to any one of the first aspects.

[0081] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is loaded by a processor to execute the steps in the medical image processing method described in any one of the first aspects.

[0082] In the embodiment of the present application, contour data and a contour reference range are obtained for the target object, normal vectors are calculated for the contour data, and the normal vectors are adjusted to a uniform orientation to obtain adjusted contour data; internal interpolation is performed on the adjusted contour data to obtain interpolated contour data; and the interpolated contour data is reconstructed to obtain a closed reconstructed medical image. In the embodiment of the present application, sufficient information is added to the upper and lower contour layers by filling and interpolating the interior of the contour composed of the contour data. Therefore, these inserted points are reconstructed as plane information during the reconstruction process, resulting in an accurate, closed manifold surface without pseudo-surfaces or holes. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0084] Figure 1 This is a schematic diagram of the structure in which a pseudo surface appears outside the contour after Poisson reconstruction in the prior art;

[0085] Figure 2 is a schematic diagram of a scenario of a medical image processing system provided by an embodiment of the present application;

[0086] Figure 3 This is a flow chart of an embodiment of a method for processing medical images provided in an embodiment of the present application;

[0087] Figure 4 In the embodiment of this application Figure 2 A flowchart of another embodiment of a method for processing medical images based on the illustrated embodiment;

[0088] Figure 5 This is a schematic structural diagram of a closed section reconstructed after interpolation of top-level contour data and bottom-level contour data in an embodiment of the present application;

[0089] Figure 6 This is a structural diagram illustrating a situation in which, after the pseudo-surface is processed in an embodiment of the present application, the holes left behind may cause the isolated surface to eventually become a non-manifold surface;

[0090] Figure 7 1 is a schematic structural diagram of an embodiment of a medical image processing device provided in an embodiment of the present application;

[0091] Figure 8 It is a schematic diagram of the structure of an embodiment of the computer device provided in the embodiments of the present application. DETAILED DESCRIPTION

[0092] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0093] In the description of the present application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the said features. In the description of the present application, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0094] In this application, the word "exemplary" is used to mean "serving as an example, illustration, or illustration." Any embodiment described in this application as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. The following description is given to enable any person skilled in the art to implement and use the present application. In the following description, details are listed for the purpose of explanation. It should be understood that one of ordinary skill in the art can recognize that the present application can be implemented without using these specific details. In other instances, well-known structures and processes are not elaborated in detail to avoid obscuring the description of the present application with unnecessary details. Therefore, the present application is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in this application.

[0095] It should be noted that since the method of the embodiment of the present application is executed in a computer device, the processing objects of each computer device exist in the form of data or information. For example, time is actually time information. It can be understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, the corresponding data exist for the computer device to process. The details will not be repeated here.

[0096] The following first introduces some basic concepts involved in the embodiments of this application:

[0097] Iterative reconstruction techniques use a series of approximate calculations to gradually approximate the image. Before reconstruction begins, the image is assumed to have uniform density. Each step in the reconstruction compares the calculated projection of the previous step with the actual measured projection, and the difference between the actual and calculated projections is used to correct the image. Each step brings the image closer to the original object, and after several corrections, a satisfactory image is obtained. However, its disadvantage is the extremely high computational workload.

[0098] Poisson reconstruction: Possion reconstruction is a mesh reconstruction method proposed by Kazhdan et al. in 2006. Possion reconstruction takes a point cloud and its normal vectors as input and produces a 3D mesh as output. Posson reconstruction is a very intuitive method. Its core concept is that a point cloud represents the positions on an object's surface, while its normal vectors represent the inside-out directions. By implicitly fitting an indicator function derived from the object, a smooth estimate of the object's surface can be obtained.

[0099] Point cloud data: Point cloud data refers to a collection of vectors in a three-dimensional coordinate system. These vectors are typically represented as (X, Y, Z) coordinates and are generally used to represent the surface shape of an object. In addition to geometric position information, point cloud data can also represent a point's RGB color, grayscale value, depth, and segmentation results.

[0100] Grid: In informatics, grid is a mechanism for integrating or sharing various geographically distributed resources (including computer systems, storage systems, communication systems, files, databases, programs, etc.) to form an organic whole and jointly complete various required tasks.

[0101] Grid container: A grid container is a storage container or storage medium for storing the grid information mentioned in the above grid concept.

[0102] The embodiments of the present application provide a medical image processing method, apparatus, computer device, and storage medium, which are described in detail below.

[0103] See also Figure 2 , Figure 2 This is a schematic diagram of a medical image processing system provided in an embodiment of the present application. The medical image processing system may include an imaging device 100 and a computer device 200. The imaging device 100 and the computer device 200 are communicatively connected, and the imaging device 100 can transmit data to the computer device 200. Figure 2 The imaging device 100 can capture medical images of the human body and output them to the computer device 200.

[0104] In the embodiment of the present application, the imaging device 100 can be a computed tomography (CT), magnetic resonance (MR), B-scan ultrasonography or other imaging equipment, etc., which is not limited here.

[0105] In the embodiments of the present application, the computer device 200 may be an independent server, or a server network or server cluster composed of servers. For example, the computer device 200 described in the embodiments of the present application includes, but is not limited to, a computer, a network host, a single network server, a set of multiple network servers, or a cloud server composed of multiple servers. A cloud server is composed of a large number of computers or network servers based on cloud computing.

[0106] In the embodiment of the present application, the computer device 200 can be a general-purpose computer device or a dedicated computer device. In a specific implementation, the computer device 200 can be a desktop computer, a portable computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, an embedded device, etc. This embodiment does not limit the type of the computer device 200.

[0107] In the embodiments of the present application, communication between the imaging device 100 and the computer device 200 can be achieved through any communication method, including but not limited to mobile communications based on the 3rd Generation Partnership Project (3GPP), Long Term Evolution (LTE), and Worldwide Interoperability for Microwave Access (WiMAX), or computer network communications based on the TCP / IP Protocol Suite (TCP / IP) and User Datagram Protocol (UDP).

[0108] Those skilled in the art will understand that Figure 2 The application environment shown in the figure is only one application scenario of the present application solution and does not constitute a limitation on the application scenario of the present application solution. Other application environments may also include Figure 2 More or fewer computer devices as shown in Figure 2 Only one computer device is shown in the figure. It can be understood that the medical image processing system can also include one or more other computer devices that can process data, which is not limited here.

[0109] In addition, if Figure 2 As shown, the medical image processing system may further include a memory 300 for storing data, such as medical image data, for example, medical image data acquired by the imaging device 100 .

[0110] It should be noted that Figure 2 The scenario diagram of the medical image processing system shown is only an example. The medical image processing system and scenario described in the embodiment of the present application are intended to more clearly illustrate the technical solution of the embodiment of the present application, and do not constitute a limitation on the technical solution provided in the embodiment of the present application. Ordinary technicians in this field can know that with the evolution of medical image processing systems and the emergence of new business scenarios, the technical solution provided in the embodiment of the present application is also applicable to similar technical problems.

[0111] First, an embodiment of the present application provides a medical image processing method, the execution subject of the medical image processing method is a medical image processing device, and the medical image processing device is applied to a computer device. The medical image processing method includes: obtaining the contour data and contour reference range of the target object; calculating the normal vector of the contour data and adjusting it to a uniform orientation to obtain adjusted contour data; performing internal interpolation on the adjusted contour data to obtain interpolated contour data; and reconstructing the interpolated contour data to obtain a closed reconstructed medical image.

[0112] like Figure 3 FIG. 1 is a flow chart of an embodiment of a method for processing medical images according to an embodiment of the present invention. The method for processing medical images includes steps 301 to 304, specifically as follows:

[0113] 301. Obtain contour data and a contour reference range of a target object.

[0114] In the embodiments of the present application, the target object can be an organ such as the heart, brain, or lungs, or a specific lesion such as a tumor target area. Of course, it is understandable that the target object can also be a human body region composed of one or more organs, or the entire human body, which is not specifically limited here.

[0115] 302. Calculate the normal vector of the contour data and adjust it to a uniform orientation to obtain adjusted contour data.

[0116] The unified direction may be a direction uniformly directed toward the inside of the target object, or a direction uniformly directed toward the outside of the target object, which is not limited here.

[0117] 303. Perform internal interpolation on the adjusted contour data to obtain interpolated contour data.

[0118] 304. Reconstruct the interpolated contour data to obtain a closed reconstructed medical image.

[0119] In the embodiment of the present application, contour data and a contour reference range are obtained for the target object, normal vectors are calculated for the contour data, and the normal vectors are adjusted to a uniform orientation to obtain adjusted contour data; internal interpolation is performed on the adjusted contour data to obtain interpolated contour data; and the interpolated contour data is reconstructed to obtain a closed reconstructed medical image. In the embodiment of the present application, sufficient information is added to the upper and lower contour layers by filling and interpolating the interior of the contour composed of the contour data. Therefore, these inserted points are reconstructed as plane information during the reconstruction process, resulting in an accurate, closed manifold surface without pseudo-surfaces or holes.

[0120] In step 301, obtaining the target object's contour data and contour reference range includes obtaining the target object's contour data and obtaining the target object's contour reference range. The target object's contour data can be acquired by an imaging device. For example, the target object's contour data can be contour data of the target object in the X, Y, and Z directions in the rectangular coordinate system.

[0121] After the contour data of the target object are acquired, the contour data of the target object are used as the basis for image reconstruction, and the set of all contour data is also the contour reference range.

[0122] In an embodiment of the present application, obtaining the contour reference range of the target object can be obtained through multi-layer slice images of the target object. Specifically, obtaining the contour reference range of the target object includes: obtaining multi-layer slice images of the target object; wherein each layer of the slice image contains contour data of the target object in a preset rectangular coordinate system, and the contour data of the target object in the preset rectangular coordinate system includes coordinate values ​​of the target object in the X-axis, Y-axis and Z-axis directions in the preset rectangular coordinate system, and the contour data of the same layer of slice images have the same coordinate value in the Z-axis direction and different coordinate values ​​in the X-axis and Y-axis directions; based on the multi-layer slice image, determining the contour reference range of the target object.

[0123] Specifically, the contour data Zmax and Zmin of the two outermost slice images of the target object in the Z-axis direction are obtained. Because medical contouring is generally performed layer by layer in parallel from the Z-axis, the range of the Z-axis can be determined according to the coordinate value of the first layer in the Z-axis direction (referred to as Z value) and the coordinate value of the last layer in the Z-axis direction. Zmin and Zmax are determined by comparing the Z values ​​of these two layers, and finally the contour reference range [Zmin, Zmax] is obtained according to Zmin and Zmax.

[0124] When the contour data of the outermost two slice images in the Z-axis direction are the maximum and minimum values ​​of the contour data of the multi-layer slice images in the Z-axis direction, then, correspondingly, determining the contour reference range of the target object based on the contour data of the outermost two slice images in the Z-axis direction includes: determining the contour reference range of the target object based on the maximum and minimum values.

[0125] After determining the maximum and minimum values ​​in the Z-axis direction, the reference range of the target object's outline can be determined. In some implementations of the present application, the range of the maximum and minimum values ​​can be directly used as the reference range of the target object's outline, for example, [Zmin, Zmax]. In other implementations of the present application, because the data is scaled during the image reconstruction process, some errors may occur, resulting in valid data not being framed, and then being deleted.

[0126] According to the basic concepts of physics, errors cannot be eliminated, only reduced. Therefore, the upper limit of the contour reference range cannot be obtained based solely on the maximum value. In practice, if only the maximum value of the contour range is used as the upper limit, when acquiring the second reconstructed medical image, there is a high probability that valid image data will be deleted, thereby losing real data. To solve this problem, in the embodiment of the present application, redundancy can be added based on the maximum and minimum values ​​in the Z-axis direction to avoid errors.

[0127] In some embodiments of the present application, determining the contour reference range of the target object based on the maximum value and the minimum value may include: increasing the maximum value by a first preset value to obtain a modified maximum value; reducing the minimum value by a second preset value to obtain a modified minimum value; and determining the contour reference range of the target object based on the modified maximum value and the modified minimum value.

[0128] For example, redundancy can be added outside the range of [Zmin, Zmax]. According to the actual experimental data of the inventor, preferably, the maximum value is increased by [0.3 to 0.5], and the modified maximum value can be recorded as Zmax+(0.3 to 0.5). Preferably, the minimum value is reduced by [0.3 to 0.5], and the modified minimum value can be recorded as Zmin-(0.3 to 0.5).

[0129] It can be understood that in actual applications, when redundancy is added outside the range of [Zmin, Zmax], only the minimum value Zmin can be redundant, for example, the contour reference range of the target object is [Zmin-(0.3~0.5), Zmax], or only the maximum value Zmax can be redundant, for example, the contour reference range of the target object is [Zmin, Zmax+(0.3~0.5)]. The specific details are not limited here.

[0130] It should be noted that if in future application scenarios, it is possible to use other reference axes for medical outlining, for example, if parallel contouring is performed layer by layer from the X-axis or Y-axis, then the contour reference range of the target object can be determined based on the contour reference range of the outermost two slice images in the X-axis direction or the contour reference range in the Y-axis direction. The determination method is similar to the determination method of the contour reference range in the Z-axis direction, and the details will not be repeated here.

[0131] In some embodiments of the present application, the internal interpolation of the contour data to obtain interpolated contour data described in the above step 303 may include: internal interpolation of the contour data to obtain initial interpolated contour data; normal vector adjustment of newly inserted contour point data in the initial interpolated contour data so that the normal vectors of the newly inserted contour points have a uniform direction to obtain interpolated contour data, wherein the normal vectors of the contour points in the adjusted contour data are in the same direction as the normal vectors of the newly inserted contour points in the interpolated contour data.

[0132] Among them, Figure 4 As shown, the internal interpolation of the contour data to obtain initial interpolated contour data may further include the following steps 401 to 403:

[0133] 401. Extract top-level contour data and bottom-level contour data from the contour data.

[0134] 402. Determine a contour point data set to be interpolated based on the top contour data and the bottom contour data.

[0135] 403. Perform internal interpolation on the contour data according to the contour point data set to obtain initial interpolated contour data.

[0136] Specifically, the step 402 of determining the contour point data set to be interpolated based on the top contour data and the bottom contour data may include: determining the interpolation contour point set corresponding to the target layer contour data, the target layer contour data including the top contour data and / or the bottom contour data, wherein the top contour data corresponds to a first interpolation contour point set, and the bottom contour data corresponds to a second interpolation contour point set; and determining the contour point data set to be interpolated based on the first interpolation contour point set and the second interpolation contour point set.

[0137] Here, determining the interpolated contour point set corresponding to the target layer contour data includes determining a first interpolated contour point set corresponding to the top layer contour data and determining a second interpolated contour point set corresponding to the bottom layer contour data. Because the methods for determining the first interpolated contour point set corresponding to the top layer contour data and the second interpolated contour point set corresponding to the bottom layer contour data are similar, the following description will use determining the first interpolated contour point set corresponding to the top layer contour data as an example.

[0138] In some embodiments of the present application, determining the first interpolation contour point set corresponding to the top-level contour data may include: determining the first contour center point of the top-level contour data; if the first contour center point is located inside the contour of the contour data, then using the first contour center point as a contour point in the first interpolation contour point set; using one contour point in the top-level contour data as a target contour point, and determining the first interpolation contour point set corresponding to the top-level contour data based on the target contour point and the first contour center point.

[0139] Furthermore, determining the first interpolation contour point set corresponding to the top-level contour data based on the target contour point and the first contour center point includes: mapping the target contour point to a two-dimensional plane to remove the data in the Z-axis direction of the target contour point to obtain the plane coordinates of the target contour point; obtaining the plane coordinates of the first contour center point; and determining the first interpolation contour point to be interpolated based on the plane coordinates of the target contour point and the plane coordinates of the first contour center point.

[0140] The method of determining the first interpolation contour point to be interpolated based on the plane coordinates of the target contour point and the plane coordinates of the first contour center point includes: connecting the target contour point with the first contour center point to obtain a contour point connecting line; calculating the length of the contour point connecting line and the slope of the contour point connecting line; and determining the first interpolation contour point to be interpolated based on the plane coordinates of the target contour point, the plane coordinates of the first contour center point, the length of the contour point connecting line, and the slope of the contour point connecting line.

[0141] Furthermore, determining the first interpolated contour point to be interpolated based on the plane coordinates of the target contour point, the plane coordinates of the first contour center point, the length of the contour point connecting line, and the slope of the contour point connecting line includes: calculating the ordinate of the first interpolated contour point based on the ordinate of the target contour point, the ordinate of the first contour center point, and the length of the contour point connecting line; and calculating the abscissa of the first interpolated contour point based on the abscissa of the target contour point, the abscissa of the first contour center point, and the slope of the contour point connecting line.

[0142] In the embodiment of the present application, linear uniform interpolation is performed with a user-defined number of interpolation points. In the embodiment of the present application, it is recommended to interpolate with an interpolation point number of 0.5 times or 0.3 times the length value. This will not be much different from the point density, and the reconstructed surface will be smoother.

[0143] In a specific embodiment of the present application, the first contour center point is used as an example to illustrate that the two-dimensional plane coordinates of the target contour point of the current cycle are known (x0, y0), the coordinates of the first contour center point are known (x1, y1), and the coordinates of the point to be interpolated are known (x i ,y i ), if the number of interpolation points is twice that of L, then according to the similar triangle theorem, we get Then the y coordinate of the point to be interpolated can be obtained as Then, according to the slope K obtained in step 4, the coordinates of the interpolation point x to be determined are x i =x0+(y i -y0)*K.

[0144] Similarly, in some embodiments of the present application, determining the second interpolation contour point set corresponding to the underlying contour data includes: determining the second contour center point of the underlying contour data; if the second contour center point is located inside the contour of the contour data, then using the second contour center point as a contour point in the second interpolation contour point set; using one contour point in the underlying contour data as a target contour point, and determining the second interpolation contour point set corresponding to the underlying contour data based on the target contour point and the second contour center point.

[0145] It should be noted that the above method of determining the second interpolation contour point set corresponding to the bottom contour data based on the bottom contour data is similar to the method of determining the first interpolation contour point set corresponding to the top contour data based on the top contour data, and will not be described in detail here.

[0146] After the above interpolation processing, closed point cloud data is obtained. However, these interpolation points do not have uniform normal vector information pointing to the outside. Therefore, in some embodiments of the present application, the normal vector of the newly inserted contour point data in the initial interpolation contour data is adjusted so that the normal vector of the newly inserted contour point is in a uniform direction, and the interpolated contour data is obtained, including: determining the Z-axis direction component of the normal vector of the newly inserted contour point data according to the maximum and minimum values ​​of the Z-axis direction component in the contour reference range, so that the normal vector of the newly inserted contour point is in a uniform direction, and the interpolated contour data is obtained, wherein the normal vector of the contour point in the adjusted contour data is in the same direction as the normal vector of the newly inserted contour point in the interpolated contour data.

[0147] Here, the newly inserted contour point data is usually newly inserted top contour point data and / or bottom contour point data.

[0148] In a specific embodiment scenario, because the newly inserted contour point data (also called interpolation points) are also parallel to the contour point data of each layer with the z-axis, and belong to the outermost layer (i.e., the top contour point data and / or the bottom contour point data), they are treated as planes during reconstruction. Therefore, the normal vectors of these contour points must be parallel to the z-axis. Therefore, it can be inferred that the normal vectors of the interpolation points can be replaced by (0, 0, ±1).

[0149] Specifically, for the contour points in the first interpolation contour point set corresponding to the top contour data, use Get the z component of the normal vector; for the contour points in the second interpolation contour point set corresponding to the underlying contour data, use Get the z component of the normal vector; finally, store the interpolated points and normal vectors obtained in the above steps one by one into the original point cloud data and the adjusted unified normal vector corresponding to the original point cloud, so that a closed point cloud data with a unified normal vector is obtained, and a closed two-dimensional manifold surface model is obtained after reconstruction. Figure 5 As shown in the figure, after the pseudo surface is processed, the holes left behind may cause the isolated surface to eventually appear as a non-manifold surface. Figure 6 As shown, it is a reconstructed image after being processed by the method of the present application, and a closed and accurately sealed two-dimensional manifold surface is obtained.

[0150] In order to better implement the medical image processing method in the embodiment of the present application, based on the medical image processing method, the embodiment of the present application also provides a medical image processing device, which is applied to a computer device, and the computer device is communicatively connected with the medical imaging device, such as Figure 7 As shown, the medical image processing device 700 includes an acquisition module 701, an adjustment module 702, an interpolation module 703 and a reconstruction module 704:

[0151] An acquisition module 701 is used to acquire the contour data and contour reference range of a target object;

[0152] An adjustment module 702 is configured to calculate a normal vector of the contour data and adjust the contour data to a uniform orientation to obtain adjusted contour data;

[0153] An interpolation module 703 is configured to perform internal interpolation on the adjusted contour data to obtain interpolated contour data;

[0154] The reconstruction module 704 is configured to reconstruct the interpolated contour data to obtain a closed reconstructed medical image.

[0155] In this embodiment of the present application, an acquisition module 701 acquires the contour data and contour reference range of a target object. An adjustment module 702 calculates a normal vector for the contour data and adjusts it to a uniform orientation to obtain adjusted contour data. An interpolation module 703 performs internal interpolation on the adjusted contour data to obtain interpolated contour data. A reconstruction module 704 reconstructs the interpolated contour data to obtain a closed reconstructed medical image. In this embodiment of the present application, sufficient information is added to the upper and lower contour layers by filling in and interpolating the interior of the contour composed of the contour data. During the reconstruction process, these interpolated points are reconstructed as plane information, resulting in an accurate, closed manifold surface free of pseudo-surfaces and holes.

[0156] In some embodiments of the present application, the contour reference range of the target object includes multi-layer slice images of the target object, wherein each layer of the slice image contains contour data of the target object in a preset rectangular coordinate system, and the contour data of the target object in the preset rectangular coordinate system includes the coordinate values ​​of the target object in the X-axis, Y-axis and Z-axis directions in the preset rectangular coordinate system. The contour data of the same layer of slice images have the same coordinate value in the Z-axis direction and different coordinate values ​​in the X-axis and Y-axis directions.

[0157] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0158] Performing internal interpolation on the contour data to obtain initial interpolated contour data;

[0159] Normal vectors of the newly inserted contour point data in the initial interpolated contour data are adjusted so that the normal vectors of the newly inserted contour points have a uniform direction, thereby obtaining interpolated contour data, wherein the normal vectors of the contour points in the adjusted contour data have the same direction as the normal vectors of the newly inserted contour points in the interpolated contour data.

[0160] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0161] Extracting top-level contour data and bottom-level contour data from the contour data;

[0162] Determine a contour point data set to be interpolated based on the top contour data and the bottom contour data;

[0163] According to the contour point data set, internal interpolation is performed on the contour data to obtain initial interpolated contour data.

[0164] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0165] Determining an interpolation contour point set corresponding to target layer contour data, the target layer contour data including the top contour data and / or the bottom contour data, wherein the top contour data corresponds to a first interpolation contour point set, and the bottom contour data corresponds to a second interpolation contour point set;

[0166] A contour point data set to be interpolated is determined according to the first interpolation contour point set and the second interpolation contour point set.

[0167] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0168] Determine the center point of the contour of the target layer contour data;

[0169] If the contour center point is located inside the contour of the contour data, the contour center point is used as a contour point in the interpolation contour point set;

[0170] A contour point in the target layer contour data is respectively used as a target contour point, and a set of interpolated contour points corresponding to the target layer contour data is determined according to the target contour point and the contour center point.

[0171] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0172] Mapping the target contour point to a two-dimensional plane to remove the data in the Z-axis direction of the target contour point to obtain the plane coordinates of the target contour point;

[0173] Obtaining the plane coordinates of the center point of the contour;

[0174] The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point and the plane coordinates of the contour center point.

[0175] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0176] Connecting the target contour point with the contour center point to obtain a contour point connecting line;

[0177] Calculating the length of the contour point connecting line and the slope of the contour point connecting line;

[0178] The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connection line, and the slope of the contour point connection line.

[0179] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0180] Calculating the ordinate of the interpolated contour point according to the ordinate of the target contour point, the ordinate of the contour center point, and the length of the line connecting the contour points;

[0181] The abscissa of the interpolated contour point is calculated according to the abscissa of the target contour point, the abscissa of the contour center point, and the slope of the line connecting the contour points.

[0182] In some implementations of the present application, the interpolation module 703 is specifically configured to:

[0183] According to the maximum and minimum values ​​of the Z-axis direction components in the contour reference range, the Z-axis direction components of the normal vectors of the newly inserted contour point data are determined so that the normal vectors of the newly inserted contour points have a uniform direction, and the interpolated contour data are obtained, wherein the normal vectors of the contour points in the adjusted contour data have the same direction as the normal vectors of the newly inserted contour points in the interpolated contour data.

[0184] The present application also provides a computer device that integrates any of the medical image processing devices provided in the present application. The computer device includes:

[0185] one or more processors;

[0186] Memory; and

[0187] One or more applications, wherein the one or more applications are stored in the memory and configured to cause the processor to execute the steps of the medical image processing method described in any of the above-mentioned medical image processing method embodiments.

[0188] The present application also provides a computer device that integrates any of the medical image processing devices provided in the present application. Figure 8 , which shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:

[0189] The computer device may include one or more processing core processors 801, one or more computer readable storage media memories 802, a power supply 803, an input unit 804 and other components. Those skilled in the art will understand that Figure 8 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0190] Processor 801 is the control center of the computer device. It connects the various components of the entire computer device using various interfaces and lines. By running or executing software programs and / or modules stored in memory 802 and accessing data stored in memory 802, it performs various functions of the computer device and processes data, thereby providing overall monitoring of the computer device. Optionally, processor 801 may include one or more processing cores. Preferably, processor 801 may integrate an application processor and a modem processor, wherein the application processor primarily processes the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 801.

[0191] The memory 802 can be used to store software programs and modules. The processor 801 executes various functional applications and data processing by running the software programs and modules stored in the memory 802. The memory 802 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 802 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory 802 may also include a memory controller to provide the processor 801 with access to the memory 802.

[0192] The computer device also includes a power supply 803 for supplying power to various components. Preferably, the power supply 803 can be logically connected to the processor 801 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The power supply 803 can also include one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0193] The computer device may further include an input unit 804, which may be configured to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0194] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 801 in the computer device will load the executable files corresponding to one or more application processes into the memory 802 according to the following instructions, and the processor 801 will run the application stored in the memory 802 to implement various functions as follows:

[0195] Obtaining the contour data and contour reference range of the target object;

[0196] Calculating the normal vector of the contour data and adjusting it to a uniform orientation to obtain adjusted contour data;

[0197] Performing internal interpolation on the adjusted contour data to obtain interpolated contour data;

[0198] The interpolated contour data is reconstructed to obtain a closed reconstructed medical image.

[0199] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0200] To this end, embodiments of the present application provide a computer-readable storage medium, which may include a read-only memory (ROM), random access memory (RAM), a disk, or an optical disk. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps of any of the medical image processing methods provided in embodiments of the present application. For example, the computer program loaded by the processor may execute the following steps:

[0201] Obtaining the contour data and contour reference range of the target object;

[0202] Calculating the normal vector of the contour data and adjusting it to a uniform orientation to obtain adjusted contour data;

[0203] Performing internal interpolation on the adjusted contour data to obtain interpolated contour data;

[0204] The interpolated contour data is reconstructed to obtain a closed reconstructed medical image.

[0205] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the detailed description of other embodiments above and will not be repeated here.

[0206] In specific implementation, the above units or structures can be implemented as independent entities, or can be arbitrarily combined to implement as the same or several entities. The specific implementation of the above units or structures can refer to the previous method embodiments and will not be repeated here.

[0207] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0208] The above is a detailed introduction to a medical image processing method, device, computer equipment and storage medium provided in the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core ideas. At the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for processing medical images, characterized in that: The medical image processing method includes: Obtaining the contour data and contour reference range of the target object; Calculating the normal vector of the contour data and adjusting it to a uniform orientation to obtain adjusted contour data; Performing internal interpolation on the adjusted contour data to obtain interpolated contour data; reconstructing the interpolated contour data to obtain a closed reconstructed medical image; The step of performing internal interpolation on the contour data to obtain interpolated contour data includes: Performing internal interpolation on the contour data to obtain initial interpolated contour data; performing normal vector adjustment on the contour point data newly inserted in the initial interpolated contour data so that the normal vectors of the newly inserted contour points have a uniform direction, thereby obtaining interpolated contour data; The internal interpolation of the contour data to obtain initial interpolation contour data includes: Extracting top-level contour data and bottom-level contour data from the contour data; determining a contour point data set to be interpolated based on the top-level contour data and the bottom-level contour data; performing internal interpolation on the contour data based on the contour point data set to obtain initial interpolated contour data; The step of determining a set of contour point data to be interpolated based on the top contour data and the bottom contour data comprises: Determining an interpolation contour point set corresponding to target layer contour data, the target layer contour data including the top contour data and / or the bottom contour data, wherein the top contour data corresponds to a first interpolation contour point set, and the bottom contour data corresponds to a second interpolation contour point set; determining a contour point data set to be interpolated based on the first interpolation contour point set and the second interpolation contour point set; The step of determining a set of interpolated contour points corresponding to the contour data of the target layer includes: Determine the contour center point of the target layer contour data; if the contour center point is located inside the contour of the contour data, use the contour center point as a contour point in an interpolated contour point set; use one contour point in the target layer contour data as a target contour point, and determine the interpolated contour point set corresponding to the target layer contour data according to the target contour point and the contour center point; the interpolated contour points of the interpolated contour point set are linearly interpolated according to the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connection line and the number of interpolated points based on the similar triangle theorem.

2. The medical image processing method according to claim 1, characterized in that: The contour reference range of the target object includes multi-layer slice images of the target object, wherein each layer of the slice image contains contour data of the target object in a preset rectangular coordinate system, and the contour data of the target object in the preset rectangular coordinate system includes coordinate values ​​of the target object in the X-axis, Y-axis and Z-axis directions in the preset rectangular coordinate system. The contour data of the same layer of slice images have the same coordinate value in the Z-axis direction and different coordinate values ​​in the X-axis and Y-axis directions.

3. The medical image processing method according to claim 2, characterized in that: The step of determining a set of interpolated contour points corresponding to the target layer contour data according to the target contour point and the contour center point includes: Mapping the target contour point to a two-dimensional plane to remove the data in the Z-axis direction of the target contour point to obtain the plane coordinates of the target contour point; Obtaining the plane coordinates of the center point of the contour; The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point and the plane coordinates of the contour center point.

4. The medical image processing method according to claim 3, characterized in that: The step of determining the interpolation contour point to be interpolated according to the plane coordinates of the target contour point and the plane coordinates of the contour center point comprises: Connecting the target contour point with the contour center point to obtain a contour point connecting line; Calculating the length of the contour point connecting line and the slope of the contour point connecting line; The interpolation contour point to be interpolated is determined according to the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connection line, and the slope of the contour point connection line.

5. The medical image processing method according to claim 4, characterized in that: The step of determining the interpolation contour point to be interpolated according to the plane coordinates of the target contour point, the plane coordinates of the contour center point, the length of the contour point connecting line, and the slope of the contour point connecting line comprises: Calculating the ordinate of the interpolated contour point according to the ordinate of the target contour point, the ordinate of the contour center point, and the length of the line connecting the contour points; The abscissa of the interpolated contour point is calculated according to the abscissa of the target contour point, the abscissa of the contour center point, and the slope of the line connecting the contour points.

6. The medical image processing method according to claim 2, characterized in that: The step of adjusting the normal vectors of the newly inserted contour point data in the initial interpolation contour data so that the normal vectors of the newly inserted contour points have a uniform orientation to obtain the interpolated contour data includes: Determining the Z-axis direction component of the normal vector of the newly inserted contour point data according to the maximum value and the minimum value of the Z-axis direction component in the contour reference range, so that the normal vector of the newly inserted contour point has a uniform direction, thereby obtaining the interpolated contour data; The normal vector of the contour point in the adjusted contour data has the same direction as the normal vector of the newly inserted contour point in the interpolated contour data.

7. A computer device, characterized in that: The computer device comprises: one or more processors; Memory; and One or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the medical image processing method according to any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the medical image processing method according to any one of claims 1 to 6.

Images