Method for extracting and processing PET / CT (positron emission tomography / computed tomography) and radiotherapy dose images of lung tumor target region

Abstract

The embodiment of the invention relates to the technical field of medical image processing, in particular to a lung tumor target PET / CT (positron emission tomography / computed tomography) and radiotherapy dose image extraction and processing method, which comprises the following steps of: extracting a tumor target image from a whole lung CT image at the early stage of radiotherapy; registering each pixel point in the tumor target region image with a pixel point in the radiotherapy dose image; registering each pixel point in the tumor target region image with pixel points in the whole lung PET image in the early stage of radiotherapy; and each pixel point in the tumor target region image is registered with the pixel points in the whole lung CT in the radiotherapy middle stage. According to the method provided by the invention, the tumor target region part can be extracted from the whole lung CT image, and data of the radiotherapy early-stage CT image, the radiotherapy middle-stage CT image, the radiotherapy early-stage PET image and the radiotherapy dose image shot by different devices are converted to the same coordinate system, so that an image data basis is provided for subsequent tumor radiotherapy reaction research.

Description

Technical Field

[0001] The present application relates to the field of medical image processing technology, and in particular to a method for extracting and processing lung tumor target area PET / CT and radiotherapy dose images. Background Art

[0002] For patients with lung tumors who receive radiotherapy, multiple PET / CT images of the entire lung are usually taken and the radiotherapy dose is set during the treatment process. However, due to the differences in the coordinate system and slice plane of the CT images taken each time, when implementing tasks such as radiotherapy response effect prediction, it is usually encountered that the pre-radiotherapy and mid-radiotherapy data, PET / CT data, and radiotherapy dose data cannot be matched one by one. In addition, the research object of tasks such as radiotherapy response effect prediction is usually only the tumor target area, which needs to be extracted from the entire lung image. We designed a method to solve this problem, extracting the tumor target area from the entire lung CT image, and converting the pre-radiotherapy CT images, mid-radiotherapy CT images, pre-radiotherapy PET images, and radiotherapy dose image data taken by different devices to the same coordinate system, providing a data basis for subsequent tumor radiotherapy response research. Summary of the invention

[0003] The present application provides a lung tumor target area PET / CT and radiotherapy dose image extraction and processing method, which extracts the tumor target area from the entire lung CT image, and converts the pre-radiotherapy CT image, mid-radiotherapy CT image, pre-radiotherapy PET image, and radiotherapy dose image data taken by different equipment into the same coordinate system, providing a data basis for subsequent tumor radiotherapy response research.

[0004] To solve the above technical problems, an embodiment of the present application provides a lung tumor target area PET / CT and radiotherapy dose image extraction and processing method, comprising the following steps: first, extracting the tumor target area image from the entire lung CT image in the early stage of radiotherapy; then, aligning each pixel point in the tumor target area image with the pixel point in the radiotherapy dose image; next, aligning each pixel point in the tumor target area image with the pixel point in the entire lung PET image in the early stage of radiotherapy; finally, aligning each pixel point in the tumor target area image with the pixel point in the entire lung CT in the middle stage of radiotherapy.

[0005] In some exemplary embodiments, a tumor target area image is extracted from an entire lung CT image before radiotherapy, including: outlining the target area with discontinuous points in the pre-radiotherapy CT image, and storing the original coordinates of the points in the pre-radiotherapy CT device coordinate system, the origin of the coordinate system, and the actual length per unit pixel; converting the original coordinates of the contour points of the outlined target area into image coordinates; filling the contour of the target area to obtain the image coordinates of all points inside the entire target area; and converting the image coordinates of all points in the entire target area back to the original coordinates in the pre-radiotherapy CT device coordinate system.

[0006] In some exemplary embodiments, the original coordinates of the outline points of the target area are converted into image coordinates, including: calculating the position of each point in the 512*512 CT image according to the original coordinates of each point in the coordinate system of the CT device before radiotherapy, and the corresponding relationship between the coordinates and the position is:

[0007] XY_img=(XY_ct1–Origin_ct1) / spacing_ct1

[0008] Among them, XY_img is the coordinate of the point in the CT image, XY_ct1 is the original coordinate of the point in the coordinate system of the CT device before radiotherapy, Origin_ct1 is the origin of the coordinate system of the CT device before radiotherapy, and spacing_ct1 is the actual length of the unit pixel point in the coordinate system of the CT device before radiotherapy.

[0009] In some exemplary embodiments, the contour of the target area is filled to obtain the image coordinates of all points inside the entire target area, including: using the OpenCV library to fill the target area contour image to obtain the image coordinates of the points inside the complete target area.

[0010] In some exemplary embodiments, the image coordinates of all points in the entire target area are converted back to the original coordinates in the coordinate system of the pre-radiotherapy CT device, including: according to the position of each point in the CT image of size 512*512, the original coordinates in the coordinate system of the pre-radiotherapy CT device are calculated, and the corresponding relationship between the coordinates and the position is:

[0011] XY_ct1=XY_img*spacing_ct1+Origin_ct1

[0012] Among them, XY_img is the coordinate of the point in the CT image, XY_ct1 is the original coordinate of the point in the coordinate system of the CT device before radiotherapy, Origin_ct1 is the origin of the coordinate system of the CT device before radiotherapy, and spacing_ct1 is the actual length of the unit pixel point in the coordinate system of the CT device before radiotherapy.

[0013] In some exemplary embodiments, each pixel point in the tumor target area image is aligned with a pixel point in the radiotherapy dose image, including: reading the coordinate values ​​of the target area portion in the radiotherapy dose image and the radiotherapy dose value; for each point in the tumor target area image, determining the smallest cuboid that contains it, and performing weighted trilinear interpolation on the radiotherapy dose value of the target object based on its vertex data, with the weight being the inverse of the distance between the target object and the vertex.

[0014] In some exemplary embodiments, each pixel point in the tumor target area image is registered with the pixel point in the entire lung PET image before radiotherapy, including: reading the coordinate value of the target area portion in the PET image; for each point in the tumor target area image, converting the point coordinates in the CT coordinate system before radiotherapy into the point coordinates in the PET coordinate system through the registration matrix; calculating the distance between each point in the target area and each point in the PET image, and selecting the PET value of the nearest point as the PET value corresponding to the target area point.

[0015] In some exemplary embodiments, for each point in the tumor target area image, the point coordinates in the pre-radiotherapy CT coordinate system are converted into point coordinates in the PET coordinate system through a registration matrix, including: forming a vector (X, Y, Z) from the point coordinates in the pre-radiotherapy CT coordinate system, multiplying it with the registration matrix to realize rotation and translation of the coordinate system, and converting it into point coordinates in the PET coordinate system.

[0016] In some exemplary embodiments, each pixel point in the tumor target area image is registered with the pixel point in the entire lung CT at the mid-stage of radiotherapy, including: reading the coordinate values ​​of the mid-stage of radiotherapy CT image points and the CT pixel values; for each point in the tumor target area image, converting the point coordinates in the pre-radiotherapy CT coordinate system into the point coordinates in the mid-stage of radiotherapy CT coordinate system through a registration matrix; for each point in the tumor target area image, determining the smallest rectangular block containing it, and performing weighted trilinear interpolation on the mid-stage of radiotherapy CT pixel values ​​of the target object according to its vertex data, with the weight being the inverse of the distance between the target object and the vertex.

[0017] In some exemplary embodiments, if there is no valid data for the eight vertices of the smallest enclosing cuboid of the target object on the grid, all grid points on the six faces of the next smallest enclosing cuboid are selected as the source of fitting data; if the next smallest enclosing cuboid still cannot accomplish the fitting task, a larger enclosing cuboid is selected, and so on, until the fitting task is accomplished.

[0018] The technical solution provided by the embodiments of the present application has at least the following advantages:

[0019] The present application proposes a lung tumor target area PET / CT, radiotherapy dose image extraction and processing method, including the following steps: first, extract the tumor target area image from the entire lung CT image in the early stage of radiotherapy; then, align each pixel in the tumor target area image with the pixel in the radiotherapy dose image; next, align each pixel in the tumor target area image with the pixel in the entire lung PET image in the early stage of radiotherapy; finally, align each pixel in the tumor target area image with the pixel in the entire lung CT in the mid-stage of radiotherapy. The method provided in the present application extracts the tumor target area portion from the entire lung CT image, and converts the pre-radiotherapy CT image, mid-radiotherapy CT image, pre-radiotherapy PET image, and radiotherapy dose image data taken by different devices to the same coordinate system, providing a data basis for subsequent tumor radiotherapy response research. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplifications do not constitute limitations on the embodiments. Unless otherwise stated, the pictures in the drawings do not constitute proportional limitations.

[0021] Figure 1 A schematic diagram of a lung tumor target area PET / CT, radiotherapy dose image extraction and processing method provided in one embodiment of the present application;

[0022] Figure 2 A schematic diagram of tumor target area CT image extraction and filling provided in an embodiment of the present application;

[0023] Figure 3 A schematic diagram of a PET image of a tumor target area provided in an embodiment of the present application;

[0024] Figure 4 A schematic diagram of a tumor target area radiotherapy dose image provided in one embodiment of the present application. DETAILED DESCRIPTION

[0025] As can be seen from the background technology, at present, the pre-radiotherapy CT images, mid-radiotherapy CT images, pre-radiotherapy PET images, and radiotherapy dose image data are taken by different devices. When implementing tasks such as radiotherapy response effect prediction, it is usually encountered that the pre-radiotherapy and mid-radiotherapy data, PET / CT data, and radiotherapy dose data cannot be matched one by one. In addition, the research object of tasks such as radiotherapy response effect prediction is usually only the tumor target area, which needs to be extracted from the entire lung image.

[0026] In view of the shortcomings of the prior art, the embodiment of the present application provides a lung tumor target area PET / CT, radiotherapy dose image extraction and processing method, comprising the following steps: first, extract the tumor target area image from the entire lung CT image in the early stage of radiotherapy; then, align each pixel in the tumor target area image with the pixel in the radiotherapy dose image; next, align each pixel in the tumor target area image with the pixel in the entire lung PET image in the early stage of radiotherapy; finally, align each pixel in the tumor target area image with the pixel in the entire lung CT in the mid-stage of radiotherapy. The purpose of the present invention is to provide a lung tumor target area PET / CT, radiotherapy dose image extraction and processing method, extract the tumor target area part from the entire lung CT image, and convert the early stage of radiotherapy CT image, mid-stage of radiotherapy CT image, early stage of radiotherapy PET image, and radiotherapy dose image data taken by different devices to the same coordinate system, so as to provide a data basis for subsequent tumor radiotherapy response research.

[0027] The following will describe the various embodiments of the present application in detail with reference to the accompanying drawings. However, it will be appreciated by those skilled in the art that in the various embodiments of the present application, many technical details are provided in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical solution claimed in the present application can be implemented.

[0028] See also Figure 1 The present application embodiment provides a lung tumor target area PET / CT, radiotherapy dose image extraction and processing method, comprising the following steps:

[0029] Step S1, extracting the tumor target area image from the whole lung CT image in the early stage of radiotherapy.

[0030] Step S2: align each pixel point in the tumor target image with the pixel point in the radiotherapy dose image.

[0031] Step S3: align each pixel point in the tumor target area image with the pixel point in the entire lung PET image before radiotherapy.

[0032] Step S4: align each pixel point in the tumor target area image with the pixel point in the entire lung CT at the middle stage of radiotherapy.

[0033] Specifically, in step S1, the tumor target area image is extracted from the entire lung CT image before radiotherapy, including the following steps: outlining the target area with discontinuous points in the pre-radiotherapy CT image, and storing the original coordinates of the points in the pre-radiotherapy CT device coordinate system, the origin of the coordinate system, and the actual length of the unit pixel; converting the original coordinates of the contour points of the outlined target area into image coordinates; filling the contour of the target area to obtain the image coordinates of all points inside the entire target area; converting the image coordinates of all points in the entire target area back to the original coordinates in the pre-radiotherapy CT device coordinate system.

[0034] It should be noted that the doctor outlines the target area from the entire lung CT image in the early stage of radiotherapy, and converts the original coordinates of the outline points of the target area into image coordinates, including: calculating the position of each point in the 512*512 CT image according to the original coordinates of each point in the coordinate system of the CT device in the early stage of radiotherapy. The corresponding relationship between the coordinates and the position is:

[0035] XY_img=(XY_ct1–Origin_ct1) / spacing_ct1

[0036] Among them, XY_img is the coordinate of the point in the CT image, XY_ct1 is the original coordinate of the point in the coordinate system of the CT device before radiotherapy, Origin_ct1 is the origin of the coordinate system of the CT device before radiotherapy, and spacing_ct1 is the actual length of the unit pixel point in the coordinate system of the CT device before radiotherapy.

[0037] It should be noted that the contour of the target area is filled to obtain the image coordinates of all points inside the entire target area, including: using the OpenCV library to fill the target area contour image to obtain the image coordinates of the points inside the complete target area.

[0038] It should be noted that the image coordinates of all points in the entire target area are converted back to the original coordinates in the coordinate system of the CT device before radiotherapy, including: according to the position of each point in the 512*512 CT image, its original coordinates in the coordinate system of the CT device before radiotherapy are calculated. The corresponding relationship between the coordinates and the position is:

[0039] XY_ct1=XY_img*spacing_ct1+Origin_ct1

[0040] Among them, XY_img is the coordinate of the point in the CT image, XY_ct1 is the original coordinate of the point in the coordinate system of the CT device before radiotherapy, Origin_ct1 is the origin of the coordinate system of the CT device before radiotherapy, and spacing_ct1 is the actual length of the unit pixel point in the coordinate system of the CT device before radiotherapy.

[0041] Specifically, in step S2, each pixel point in the tumor target area image (CT image of the tumor target area before radiotherapy) is aligned with the pixel point in the radiotherapy dose image, including: reading the coordinate value of the target area part in the radiotherapy dose image and the radiotherapy dose value; for each point in the tumor target area image, determining the smallest cuboid containing it, and performing weighted trilinear interpolation on the radiotherapy dose value of the target object according to its vertex data, and the weight is taken as the inverse of the distance between the target object and the vertex.

[0042] It should be noted that for the problem of missing data, there may be a situation where the eight vertices of the smallest enclosing cuboid of the target object on the grid have no valid data. In this case, consider a larger enclosing cuboid and select all the grid points on the six faces of the next smaller enclosing cuboid as the source of fitting data. If the next smaller enclosing cuboid still cannot achieve the fitting task, take a larger enclosing cuboid, and so on, until the fitting task is achieved.

[0043] Specifically, in step S3, each pixel point in the tumor target area image is registered with the pixel point in the entire lung PET image before radiotherapy, including: reading the coordinate value of the target area part in the PET image; for each point in the tumor target area image, converting the point coordinates in the CT coordinate system before radiotherapy into the point coordinates in the PET coordinate system through the registration matrix; calculating the distance between each point in the target area and each point in the PET image, and selecting the PET value of the nearest point as the PET value corresponding to the target area point.

[0044] It should be noted that for each point in the pre-radiotherapy CT target image, the point coordinates in the pre-radiotherapy CT coordinate system are converted into point coordinates in the PET coordinate system through the registration matrix, including: forming a vector (X, Y, Z) from the point coordinates in the pre-radiotherapy CT coordinate system, multiplying it with the registration matrix, realizing the rotation and translation of the coordinate system, and converting it into the point coordinates in the PET coordinate system.

[0045] Specifically, in step S4, each pixel point in the tumor target image is aligned with the pixel point in the entire lung CT in the mid-stage radiotherapy, including: reading the coordinate values ​​of the mid-stage radiotherapy CT image points and the CT pixel values; for each point in the early stage radiotherapy CT target image, converting the point coordinates in the early stage radiotherapy CT coordinate system into the point coordinates in the mid-stage radiotherapy CT coordinate system through the alignment matrix; for each point in the early stage radiotherapy CT target image, determining the smallest rectangular block containing it, and performing weighted trilinear interpolation on the mid-stage radiotherapy CT pixel value of the target object according to its vertex data, and the weight is taken as the inverse of the distance between the target object and the vertex.

[0046] It should be noted that for the data missing problem, there may be a situation where the eight vertices of the smallest enclosing cuboid of the target object on the grid have no valid data. In this case, consider its larger enclosing cuboid and select all the grid points on the six faces of the smaller enclosing cuboid as the source of fitting data. If the smaller enclosing cuboid still cannot achieve the fitting task, then take a larger enclosing cuboid, and so on, until the fitting task is achieved.

[0047] The lung tumor target area PET / CT, radiotherapy dose image extraction and processing method provided by the present application are described in detail with respect to a specific embodiment below.

[0048] First, the lung tumor target area PET / CT, radiotherapy dose image extraction and processing method proposed in the embodiment of the present application is based on the Windows 10 system, implemented using Python 3.9, and using the CUDA API for calculation acceleration.

[0049] In addition, it should be noted that the tumor image data in the embodiment of the present application are PET / CT and radiotherapy dose images of non-small cell lung cancer before and during radiotherapy.

[0050] First, the tumor target area image is extracted from the whole lung CT image before radiotherapy. The tumor target area image is formed by the doctor's outline. Figure 2 .

[0051] Then, each pixel point in the tumor target area image (CT image of the tumor target area before radiotherapy) is registered with the pixel point in the radiotherapy dose image.

[0052] Next, each pixel in the CT image of the tumor target area before radiotherapy is aligned with the pixel in the PET image of the entire lung before radiotherapy.

[0053] Finally, each pixel in the CT image of the tumor target area in the early stage of radiotherapy is registered with the pixel in the entire lung CT image in the middle stage of radiotherapy.

[0054] See also Figure 3 and Figure 4 , Figure 3 A schematic diagram of a PET image of a tumor target area provided in one embodiment of the present application. Figure 4 A schematic diagram of a tumor target area radiotherapy dose image provided in an embodiment of the present application. Figure 2 , Figure 3 and Figure 4It can be seen that the lung tumor target area PET / CT, radiotherapy dose image extraction and processing method provided by this application extracts the tumor target area from the entire lung CT image, and converts the pre-radiotherapy CT image, mid-radiotherapy CT image, pre-radiotherapy PET image, and radiotherapy dose image data taken by different equipment to the same coordinate system, providing a data basis for subsequent tumor radiotherapy response research. And the method of this application has been tested, proving the effectiveness of the method of this application.

[0055] Based on the above technical scheme, the embodiment of the present application provides a lung tumor target area PET / CT, radiotherapy dose image extraction and processing method, the method comprising the following steps: first, extract the tumor target area image from the entire lung CT image in the early stage of radiotherapy; then, align each pixel in the tumor target area image with the pixel in the radiotherapy dose image; next, align each pixel in the tumor target area image with the pixel in the entire lung PET image in the early stage of radiotherapy; finally, align each pixel in the tumor target area image with the pixel in the entire lung CT in the mid-stage of radiotherapy. The method provided in the present application extracts the tumor target area portion from the entire lung CT image, and converts the pre-radiotherapy CT image, mid-radiotherapy CT image, pre-radiotherapy PET image, and radiotherapy dose image data taken by different devices to the same coordinate system, providing a data basis for subsequent tumor radiotherapy response research.

[0056] Those skilled in the art can understand that the above-mentioned embodiments are specific examples for implementing the present application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of the present application. Any person skilled in the art can make their own changes and modifications without departing from the spirit and scope of the present application, so the scope of protection of the present application shall be based on the scope defined in the claims.

Claims

1. A lung tumor target area PET / CT, radiotherapy dose image extraction and processing method, characterized in that: The following steps are involved: Extract tumor target images from the whole lung CT images before radiotherapy; Registering each pixel point in the tumor target image with the pixel point in the radiotherapy dose image; Registering each pixel in the tumor target image with the pixel in the entire lung PET image before radiotherapy; Each pixel point in the tumor target area image is registered with the pixel point in the whole lung CT in the middle stage of radiotherapy.

2. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 1, characterized in that: Extract tumor target images from the entire lung CT images before radiotherapy, including: In the pre-radiotherapy CT image, the target area is outlined with discontinuous points, and the original coordinates of the points in the pre-radiotherapy CT device coordinate system, the origin of the coordinate system, and the actual length of the unit pixel are stored; Convert the original coordinates of the outline points of the target area into image coordinates; Fill the outline of the target area to obtain the image coordinates of all points inside the entire target area; The image coordinates of all points in the entire target area are converted back to the original coordinates in the coordinate system of the CT device before radiotherapy.

3. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 2, characterized in that: The original coordinates of the outlined target area points are converted into image coordinates, including: According to the original coordinates of each point in the coordinate system of the CT device before radiotherapy, its position in the 512*512 CT image is calculated. The corresponding relationship between the coordinates and the position is: XY_img=(XY_ct1–Origin_ct1) / spacing_ct1 Among them, XY_img is the coordinate of the point in the CT image, XY_ct1 is the original coordinate of the point in the coordinate system of the CT device before radiotherapy, Origin_ct1 is the origin of the coordinate system of the CT device before radiotherapy, and spacing_ct1 is the actual length of the unit pixel point in the coordinate system of the CT device before radiotherapy.

4. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 2, characterized in that: Fill the outline of the target area to obtain the image coordinates of all points inside the entire target area, including: The OpenCV library is used to fill the target area contour image and obtain the image coordinates of the internal points of the complete target area.

5. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 2, characterized in that: The image coordinates of all points in the entire target area are converted back to the original coordinates in the coordinate system of the CT device before radiotherapy, including: According to the position of each point in the 512*512 CT image, its original coordinates in the coordinate system of the CT device before radiotherapy are calculated. The corresponding relationship between the coordinates and the position is: XY_ct1=XY_img*spacing_ct1+Origin_ct1 Among them, XY_img is the coordinate of the point in the CT image, XY_ct1 is the original coordinate of the point in the coordinate system of the CT device before radiotherapy, Origin_ct1 is the origin of the coordinate system of the CT device before radiotherapy, and spacing_ct1 is the actual length of the unit pixel point in the coordinate system of the CT device before radiotherapy.

6. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 1, characterized in that: Registering each pixel point in the tumor target image with the pixel point in the radiotherapy dose image includes: Read the coordinate values ​​of the target area and the radiotherapy dose value in the radiotherapy dose image; For each point in the tumor target image, the smallest cuboid containing it is determined, and the radiotherapy dose value of the target object is subjected to weighted trilinear interpolation according to its vertex data, with the weight being the inverse of the distance between the target object and the vertex.

7. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 1, characterized in that: Registering each pixel in the tumor target image with the pixel in the entire lung PET image before radiotherapy, including: Read the coordinate values ​​of the target area in the PET image; For each point in the tumor target area image, the point coordinates in the pre-radiotherapy CT coordinate system are converted into the point coordinates in the PET coordinate system through a registration matrix; Calculate the distance between each point in the target area and each point in the PET image, and select the PET value of the nearest point as the PET value corresponding to the target point.

8. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 7, characterized in that: For each point in the tumor target image, the point coordinates in the pre-radiotherapy CT coordinate system are converted into the point coordinates in the PET coordinate system through the registration matrix, including: The point coordinates in the CT coordinate system before radiotherapy are formed into a vector (X, Y, Z), which is multiplied by the registration matrix to realize the rotation and translation of the coordinate system and converted into the point coordinates in the PET coordinate system.

9. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 1, characterized in that: Each pixel point in the tumor target image is registered with the pixel point in the entire lung CT in the middle of radiotherapy, including: Read the coordinate values ​​of CT image points and CT pixel values ​​during the interim period of radiotherapy; For each point in the tumor target image, the point coordinates in the early stage of radiotherapy CT coordinate system are converted into the point coordinates in the mid-stage of radiotherapy CT coordinate system through a registration matrix; For each point in the tumor target image, the smallest cuboid containing it is determined, and weighted trilinear interpolation is performed on the mid-term radiotherapy CT pixel value of the target object according to its vertex data, with the weight being the inverse of the distance between the target object and the vertex.

10. The lung tumor target area PET / CT and radiotherapy dose image extraction and processing method according to claim 9, characterized in that: If there is no valid data for the eight vertices of the smallest enclosing cuboid of the target object on the grid, all grid points on the six faces of the next smallest enclosing cuboid are selected as the source of fitting data. If the next smallest enclosing cuboid still cannot achieve the fitting task, a larger enclosing cuboid is selected, and so on, until the fitting task is achieved.

Images