A method and system for optimizing the generation of lattice target areas

Abstract

The present invention discloses a method and system for generating and optimizing a lattice target volume. The method comprises: importing a DICOM file of a tumor patient and obtaining a tumor CT image coordinate system and a tumor target volume contour; determining the diameter parameters, spacing parameters, and indentation boundary of the lattice target volume based on the volume of the tumor target volume contour; generating a closest-packed sphere distribution of the lattice target volume in the tumor CT image coordinate system based on the diameter and spacing parameters of the lattice target volume; performing nested iterative optimization of the sphere center three-dimensional coordinate matrix using translation and rotation operators to obtain an optimal result; and generating a corresponding lattice target volume outline based on the optimal result. The system includes a data acquisition module, a parameter confirmation module, a lattice target volume generation module, a lattice target volume optimization module, and an optimization result output module. The present invention can automatically determine the size and spacing of the lattice target volume based on the target volume, generating an accurate and reasonable lattice target volume distribution. The present invention can be widely applied in the field of radiotherapy technology.

Description

Technical Field

[0001] The present invention relates to the technical field of radiotherapy, and in particular to a method and system for optimizing the generation of a lattice target area. Background Art

[0002] The primary goal of tumor radiotherapy is to eradicate the tumor while minimizing radiation damage to normal tissues to preserve their normal metabolic function. However, conventional fractionated radiotherapy is not ideal for large or radioresistant tumors, resulting in significant radiation damage to normal tissues, further reducing the effectiveness of radiotherapy. Spatially fractionated radiotherapy (SFRT) delivers a very high prescription dose (typically 12 Gy to 25 Gy) to the target volume through a single or very few radiotherapy sessions. This creates a spatially staggered distribution of high and low doses within the target volume, thereby minimizing radiation damage to normal tissues while increasing the target volume to achieve significant tumor regression. Previous studies have demonstrated that spatially fractionated radiotherapy has demonstrated good safety and efficacy in clinical practice for multiple sites, including large head and neck tumors, lung cancer, liver metastases, and cervical cancer. It has low toxicity and side effects, and high rates of complete response (CR) or partial response (PR) based on current imaging techniques, demonstrating its broad clinical application. Preliminary mechanistic studies have shown that the clinical advantages of spatially fractionated radiotherapy lie primarily in three biological response mechanisms: the bystander effect, the vascular effect, and the immune regulation mechanism. This staggered distribution of high-dose peaks and low-dose troughs may synergistically enhance the anti-tumor immune effect. Specifically, the peak dose in the regular dose distribution is high enough to induce a tumor-specific immune response, while the trough dose is low enough to protect tumor microvasculature and perfusion, allowing the circulation of cytokines, chemokines, and immunogenic factors, thereby synergistically inducing anti-tumor immunity. Therefore, spatially fractionated radiotherapy is considered the most promising and innovative technology for treating large malignant tumors, subverting the concept of uniform dose in conventional radiotherapy.

[0003] Currently, there are many radiotherapy techniques for achieving the special dose distribution of spatially fractionated radiotherapy in clinical practice, and there is no broad consensus on how to generate the optimal physical parameters of the lattice target area. However, based on the published and reported literature, the following methods can be summarized:

[0004] (1) Grid-based two-dimensional irradiation technology. This is an early and commonly used spatial fractionation radiotherapy technology, which uses high-density alloy materials to be precisely processed into a two-dimensional grid collimator with distributed circular holes in a two-dimensional array. It is placed under the accelerator head to form multiple small narrow beams to irradiate the tumor, forming a two-dimensional irradiation in the form of alternating high and low doses on the cross section perpendicular to the beam.

[0005] (2) Grid-based three-dimensional irradiation technology: Based on the aforementioned two-dimensional technology, two perpendicular gantry angles are selected for irradiation to generate a high- and low-dose alternating distribution in three-dimensional space.

[0006] (3) Accelerator-based multi-leaf collimator irradiation technology. That is, the multi-leaf collimator (MLC) is used to form multiple square small fields with equal spacing in a chessboard pattern to replace the grid collimator to irradiate the tumor and achieve a two-dimensional or three-dimensional grid dose distribution.

[0007] (4) By manually outlining the lattice target area, the distribution of spatially segmented dose is achieved using the inverse optimization algorithm of modern intensity-modulated technology.

[0008] The disadvantages of the above-mentioned grid-based two-dimensional and three-dimensional irradiation technologies are that the production process is cumbersome and the aperture sizes are limited to a few. The aperture size and spacing cannot be freely and quickly adjusted according to the size, morphology, and location depth of the tumor, making it difficult to reduce radiotherapy damage to normal tissues around the target area. Irradiation technology based on accelerator multi-leaf collimators also has the problem of only being able to generate a fixed-size radiation field (the MLC leaf width is typically 0.5 cm, and it can generate small square fields that are integer multiples of 0.5 cm), and the adjustability of the radiation field size and spacing is poor. Therefore, the existing technology suffers from the problem of poor adjustability of the size and spacing of the lattice target area. Summary of the Invention

[0009] In order to solve the above technical problems, the purpose of the present invention is to provide a method and system for optimizing the generation of lattice target areas, which can automatically determine the size and spacing of lattice target areas according to the target area volume size and generate accurate and reasonable lattice target area distribution.

[0010] The first technical solution adopted by the present invention is: a method for generating and optimizing a lattice target region, comprising the following steps:

[0011] Import the DICOM file of the tumor patient and obtain the tumor CT image coordinate system and tumor target volume contour;

[0012] determining a diameter parameter, a spacing parameter, and an indentation boundary of a lattice target region based on the volume of the tumor target volume contour;

[0013] generating a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area, and obtaining a three-dimensional coordinate matrix of the sphere center;

[0014] Performing nested iterative optimization on the sphere center three-dimensional coordinate matrix based on translation operators and rotation operators, and taking the number of lattice target areas contained in the indented boundary as an optimization evaluation criterion to obtain an optimal result;

[0015] Generate the corresponding lattice target outline based on the optimal result.

[0016] Furthermore, the diameter parameter and spacing parameter of the lattice target area are expressed as follows:

[0017]

[0018] Among them, V T It represents the volume of the tumor target volume contour; Radius represents the diameter parameter of the lattice target area; Dist represents the spacing parameter of the lattice target area.

[0019] Furthermore, the retracted boundary of the lattice target area is a range boundary limiting the lattice target area, and isotropic retraction is performed according to the volume size of the tumor target volume contour to form the boundary of the tumor target volume contour grid structure.

[0020] The step of generating a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area to obtain a three-dimensional coordinate matrix of the sphere center specifically includes:

[0021] determining the three-dimensional size and geometric center coordinate position of the tumor target volume in the tumor target volume coordinate system based on the tumor target volume contour;

[0022] Taking the geometric center coordinate position as the center and the maximum value of the three-dimensional size times as the side length, generating an initial boundary limit range of a lattice target area with a maximized cube shape in the tumor CT image coordinate system;

[0023] Within the initial boundary range, with the geometric center coordinate position as the center, a closest packed sphere distribution is generated based on the diameter parameter and spacing parameter of the lattice target area to obtain a sphere center three-dimensional coordinate matrix.

[0024] Furthermore, the algorithm for generating the closest packed sphere distribution specifically includes:

[0025] Determining the arrangement of the closest packed spheres, the radius of the spheres, and the spacing in three dimensions based on the closest spatial arrangement of atoms;

[0026] Based on the spacing in the three-dimensional direction, the coordinate position of the center of the lattice target area is generated layer by layer from bottom to top along the z-axis.

[0027] Furthermore, the step of performing nested iterative optimization on the sphere center three-dimensional coordinate matrix based on the translation operator and the rotation operator, and taking the number of lattice target areas contained in the indented boundary as the optimization evaluation criterion to obtain the optimal result, specifically includes:

[0028] Initializing the 3D coordinate matrix of the sphere center to obtain a data set containing the 3D structure of the lattice target area;

[0029] performing nested iterative optimization on the data set based on a translation operator and a rotation operator;

[0030] Calculating the number of lattice target area distributions contained in the shrinking boundary at each nesting iteration, and recording the operator parameters corresponding to the maximum number of target area distributions;

[0031] The three-dimensional coordinate matrix of the sphere center is modified based on the operator parameters to obtain an optimal result.

[0032] Furthermore, the translation operator is expressed as follows:

[0033]

[0034] Among them, t x , t y and t z Represents the offset in the x-axis, y-axis, and z-axis directions respectively.

[0035] Furthermore, the rotation operator is expressed as follows:

[0036] Rotation operator around the X axis:

[0037]

[0038] Rotation operator around the Y axis:

[0039]

[0040] Rotation operator around the Z axis:

[0041]

[0042] Among them, α, β and γ represent the angles of rotation around the x-axis, y-axis and z-axis respectively; p x 、p y and p z They represent the three-dimensional coordinate components of the rotation point of the lattice matrix respectively.

[0043] The second technical solution adopted by the present invention is: a lattice target area generation optimization system, comprising:

[0044] The data acquisition module is used to import the DICOM files of tumor patients and obtain the tumor CT image coordinate system and tumor target volume contour;

[0045] a parameter confirmation module, which determines a diameter parameter, a spacing parameter, and an indentation boundary of a lattice target region based on the volume of the tumor target volume contour;

[0046] a lattice target area generation module, which generates a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area, and obtains a three-dimensional coordinate matrix of the sphere center;

[0047] A lattice target area optimization module performs nested iterative optimization on the sphere center three-dimensional coordinate matrix based on translation operators and rotation operators, and uses the number of lattice target area distributions contained in the indented boundary as an optimization evaluation criterion to obtain the optimal result;

[0048] The optimization result output module generates the corresponding lattice target area outline based on the optimal result.

[0049] The method and system of the present invention have the following beneficial effects: Based on the principle of stacking two layers of regular, tightly packed structures, the present invention achieves an optimal lattice structure distribution through iterative optimization, generating an optimal lattice target volume for spatially fractionated radiotherapy. Compared to existing technologies, the size and spacing of lattice targets can be automatically determined based on the target volume, allowing for automated and rapid target delineation, eliminating the variability in manual delineation decisions and heterogeneity in delineation results. The lattice target volume obtained through iterative optimization is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flow chart of the steps of a method for generating and optimizing a lattice target region according to the present invention;

[0051] Figure 2 It is a structural block diagram of a lattice target area generation optimization system of the present invention;

[0052] Figure 3 This is a schematic diagram of the distribution of densely packed spheres in a lattice target area according to a method for optimizing the generation of a lattice target area of ​​the present invention;

[0053] Figure 4 It is a schematic diagram of the spherical center coordinates of the most densely packed spheres distributed in the lattice target area of ​​a method for generating and optimizing the lattice target area of ​​the present invention;

[0054] Figure 5 It is an execution flow chart of a method for generating and optimizing a lattice target region according to the present invention. DETAILED DESCRIPTION

[0055] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are provided for ease of description only and do not limit the order of the steps. The order of execution of the steps in the embodiments can be adaptively adjusted based on the understanding of those skilled in the art.

[0056] Reference Figure 1 and Figure 5 The present invention provides a method for optimizing the generation of a lattice target region, the method comprising the following steps:

[0057] S1. Import the DICOM file of the tumor patient and obtain the tumor CT image coordinate system and tumor target volume contour;

[0058] Specifically, after a patient with a large tumor undergoes a CT scan, the radiation oncologist refers to other functional imaging data to complete the delineation of normal tissue and tumor target volume (GTV) on the acquired CT image and stores it in a DICOM file; the present invention obtains the tumor CT image coordinate system and tumor target volume contour by importing the DICOM file of the tumor patient.

[0059] S2. determining a diameter parameter, a spacing parameter, and an indentation boundary of a lattice target region based on the volume of the tumor target volume contour;

[0060] Specifically, isotropically shrinking the tumor target volume contour by 1 to 2 cm according to the volume size of the tumor target volume contour is performed to form a tumor target volume contour lattice structure (GTV-Lattice), thereby obtaining the shrinking boundary of the lattice target area; the shrinking boundary of the lattice target area is used to limit the automatically generated range boundary of the lattice target area.

[0061] Based on the volume of the tumor target volume contour, the diameter parameter and spacing parameter of the lattice target area are determined using the following discriminator algorithm, which are expressed as follows:

[0062]

[0063] Among them, V T It represents the volume of the tumor target volume contour; Radius represents the diameter parameter of the lattice target area; Dist represents the spacing parameter of the lattice target area.

[0064] S3, generating a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area, and obtaining a three-dimensional coordinate matrix of the sphere center;

[0065] S3.1. Determine the three-dimensional size and geometric center coordinate position of the tumor target volume in the tumor target volume coordinate system based on the tumor target volume contour; the size on the x-axis is expressed as X T Indicates; the size on the y-axis is indicated by Y T Indicates that the size on the z-axis is represented by Z T Indicates that the geometric center coordinate position is expressed as P0(x0,y0,z0).

[0066] S3.2, taking the geometric center coordinate position as the center and the maximum value of the three-dimensional size times as the side length, generating a lattice target area boundary of a maximized cube shape in the tumor CT image coordinate system to obtain an initial boundary range;

[0067] Specifically, the expression of the side length is as follows:

[0068]

[0069] Here, length represents the side length.

[0070] The transformation relationship between the geometric center coordinate position in the tumor CT image coordinate system and the geometric center coordinate position in the tumor target volume coordinate system is (x+x0, y+y0, z+z0).

[0071] S3.3. Within the initial boundary range, with the geometric center coordinate position as the center, generate a densest packed sphere distribution based on the diameter parameters and spacing parameters of the lattice target area to obtain a three-dimensional coordinate matrix of the sphere center.

[0072] S3.3.1. Determine the arrangement of the closest-packed spheres, the radius of the spheres, and the three-dimensional spacing based on the closest spatial arrangement of atoms;

[0073] Specifically, the most densely packed sphere distribution of the present invention refers to the most dense spatial arrangement of atoms in solid state physics, which has been proven to be the most dense distribution in three-dimensional space known to date. Figure 3 The basic unit is a two-layer structure stacked together. On the same layer, each ball is in contact with 6 balls around it. Figure 3 The upper layer of the result is shown in the figure; it contacts 3 balls on the upper and lower layers respectively, so each ball contacts 12 balls in three-dimensional space. The radius r of the ball is half of the spacing parameter Dist of the lattice target area; the radius R0 of the lattice target area is half of the diameter parameter Radius of the lattice target area; the spacing in the x-axis direction is 2r; the spacing in the y-axis direction is The spacing in the z-axis direction is

[0074] S3.3.2. Based on the spacing in the three-dimensional direction, the coordinate position of the center of the lattice target area is generated layer by layer from bottom to top along the z-axis.

[0075] Specifically, refer to Figure 4 Based on the above parameters, the coordinate position of the sphere center of the lattice target area is generated layer by layer from bottom to top along the z-axis. The algorithm process includes:

[0076] The number of layers in the z-axis direction is represented by k, and its value range is Here, length represents the side length.

[0077] When k is an odd number, the coordinate position of the lattice target area center is determined according to the following rules:

[0078] If the number of layers in the y-axis direction is j, its value range is When j is an odd number, the coordinate position of the sphere center of the lattice target area is calculated as follows:

[0079]

[0080] Among them, P(x,y,z) represents the coordinate position of the center of the lattice target area; r represents the radius of the sphere; i represents the layer number in the x-axis direction; j represents the layer number in the y-axis direction; k represents the layer number in the z-axis direction.

[0081] If the number of layers j in the y-axis direction is in the range When j is an even number, the coordinate position of the lattice target area center is calculated as follows:

[0082]

[0083] If the number of layers j in the y-axis direction is in the range When j is an odd number, the coordinate position of the sphere center of the lattice target area is calculated as follows:

[0084]

[0085] If the number of layers j in the y-axis direction is in the range When j is an even number, the coordinate position of the lattice target area center is calculated as follows:

[0086]

[0087] When k is an even number, the coordinate position of the lattice target area center is determined according to the following rules:

[0088] If j is an odd number, the coordinate position of the lattice target area center is calculated as follows:

[0089]

[0090] If j is an odd number, the coordinate position of the lattice target area center is calculated as follows:

[0091]

[0092] Through the above algorithm process, the three-dimensional coordinate matrix P of the sphere centers of the densest packed sphere distribution in the lattice target area can be generated.

[0093] S4, performing nested iterative optimization on the sphere center three-dimensional coordinate matrix based on a translation operator and a rotation operator, and using the number of lattice target regions contained in the indented boundary as an optimization evaluation criterion to obtain an optimal result;

[0094] Specifically, the spherical center coordinate three-dimensional matrix obtained in step S3 is regular, while the shape of the tumor target volume is diverse. The spatial matching relationship between the two still needs to be further optimized in order to achieve the best effect.

[0095] S4.1. Initializing the 3D coordinate matrix of the sphere center to obtain a data set containing the 3D structure of the lattice target area;

[0096] Specifically, with each point of the spherical center three-dimensional coordinate matrix P as the sphere center and R0 as the radius, a spherical formula is used to generate a data set P-lattice containing the three-dimensional structure of the lattice target area; the spherical formula is expressed as follows:

[0097] (x-Px) 2 +(y-Py) 2 +(z-Pz) 2 =r0 2

[0098] Among them, x, y and z represent the X-axis, Y-axis and Z-axis components of the lattice spherical target area outline coordinates respectively; Px, Py and Pz represent the X-axis, Y-axis and Z-axis components of the spherical center coordinates of the lattice spherical target area respectively.

[0099] S4.2. performing nested iterative optimization on the data set based on a translation operator and a rotation operator;

[0100] Specifically, the translation operator is expressed as follows:

[0101]

[0102] Among them, t x , t y and t z Represents the offset in the x-axis, y-axis and z-axis directions respectively, and its value range is [-R0:1mm:R0].

[0103] The rotation operator is expressed as follows:

[0104] Rotation operator around the X axis:

[0105]

[0106] Rotation operator around the Y axis:

[0107]

[0108] Rotation operator around the Z axis:

[0109]

[0110] Among them, α, β and γ represent the angles of rotation around the x-axis, y-axis and z-axis respectively, and their value range is [-90°: 1°: 90°]; p x 、p y and p z They represent the three-dimensional coordinate components of the rotation point of the lattice matrix respectively.

[0111] S4.3. Calculate the number of lattice target distributions contained in the indented boundary at each nesting iteration, and record the operator parameters corresponding to the maximum number of lattice target distributions;

[0112] S4.4. Modify the sphere center three-dimensional coordinate matrix based on the operator parameters to obtain the optimal result.

[0113] S5. Generate corresponding lattice target area outline based on the optimal result.

[0114] Specifically, the outer lattice in the optimal result is removed by using the inward-shrinking boundary, and only the inner lattice distribution is retained.

[0115] Reference Figure 2 The present invention provides a system for optimizing the generation of a lattice target region, comprising:

[0116] The data acquisition module is used to import the DICOM files of tumor patients and obtain the tumor CT image coordinate system and tumor target volume contour;

[0117] a parameter confirmation module, which determines a diameter parameter, a spacing parameter, and an indentation boundary of a lattice target region based on the volume of the tumor target volume contour;

[0118] a lattice target area generation module, which generates a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area, and obtains a three-dimensional coordinate matrix of the sphere center;

[0119] A lattice target area optimization module performs nested iterative optimization on the sphere center three-dimensional coordinate matrix based on translation operators and rotation operators, and uses the number of lattice target area distributions contained in the indented boundary as an optimization evaluation criterion to obtain the optimal result;

[0120] The optimization result output module generates the corresponding lattice target area outline based on the optimal result.

[0121] The contents of the above method embodiments are all applicable to the present system embodiments. The functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0122] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A method for optimizing the generation of a lattice target region, characterized in that: The following steps are involved: Import the DICOM file of the tumor patient and obtain the tumor CT image coordinate system and tumor target volume contour; determining a diameter parameter, a spacing parameter, and an indentation boundary of a lattice target region based on the volume of the tumor target volume contour; Based on the volume of the tumor target volume contour, the diameter parameter and spacing parameter of the lattice target area are determined using the following discriminator algorithm, which are expressed as follows: Among them, V T Indicates the volume of the tumor target volume contour; Radius indicates the diameter parameter of the lattice target area; Dist indicates the spacing parameter of the lattice target area; generating a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area, and obtaining a three-dimensional coordinate matrix of the sphere center; Performing nested iterative optimization on the sphere center three-dimensional coordinate matrix based on translation operators and rotation operators, and taking the number of lattice target areas contained in the indented boundary as an optimization evaluation criterion to obtain an optimal result; Generate corresponding lattice target area outline based on the optimal result; The step of generating a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area to obtain a three-dimensional coordinate matrix of the sphere center specifically includes: determining the three-dimensional size and geometric center coordinate position of the tumor target volume in the tumor target volume coordinate system based on the tumor target volume contour; Taking the geometric center coordinate position as the center and the maximum value of the three-dimensional size times as the side length, generating an initial boundary limit range of a lattice target area with a maximized cube shape in the tumor CT image coordinate system; Within the initial boundary range, taking the geometric center coordinate position as the center, generating a closest-packed sphere distribution based on the diameter parameter and spacing parameter of the lattice target area to obtain a sphere center three-dimensional coordinate matrix; The step of performing nested iterative optimization on the sphere center three-dimensional coordinate matrix based on the translation operator and the rotation operator, and taking the number of lattice target areas contained in the indented boundary as the optimization evaluation criterion to obtain the optimal result, specifically includes: Initializing the 3D coordinate matrix of the sphere center to obtain a data set containing the 3D structure of the lattice target area; performing nested iterative optimization on the data set based on a translation operator and a rotation operator; Calculating the number of lattice target area distributions contained in the shrinking boundary at each nesting iteration, and recording the operator parameters corresponding to the maximum number of lattice target area distributions; Correcting the sphere center three-dimensional coordinate matrix based on the operator parameters to obtain an optimal result; The translation operator is expressed as follows: Among them, t x , t y and t z Represents the offset in the x-axis, y-axis and z-axis directions respectively; The rotation operator is expressed as follows: Rotation operator around the X axis: Rotation operator around the Y axis: Rotation operator around the Z axis: Among them, α, β and γ represent the angles of rotation around the x-axis, y-axis and z-axis respectively; p x 、p y and p z They represent the three-dimensional coordinate components of the rotation point of the lattice matrix respectively.

2. The method for optimizing the generation of a lattice target region according to claim 1, characterized in that: The inward contraction boundary of the lattice target area is a range boundary limiting the lattice target area, and isotropically contracted according to the volume size of the tumor target volume contour to form the boundary of the tumor target volume contour grid structure.

3. The method for optimizing the generation of a lattice target region according to claim 1, characterized in that: The algorithm for generating the densest packed sphere distribution specifically includes: Determining the arrangement of the closest packed spheres, the radius of the spheres, and the spacing in three dimensions based on the closest spatial arrangement of atoms; Based on the spacing in the three-dimensional direction, the coordinate position of the center of the lattice target area is generated layer by layer from bottom to top along the z-axis.

4. A lattice target area generation optimization system, characterized in that: A method for performing a generation optimization method of a lattice target region as claimed in claim 1, comprising: The data acquisition module is used to import the DICOM files of tumor patients and obtain the tumor CT image coordinate system and tumor target volume contour; a parameter confirmation module, which determines a diameter parameter, a spacing parameter, and an indentation boundary of a lattice target region based on the volume of the tumor target volume contour; a lattice target area generation module, which generates a densely packed sphere distribution of the lattice target area in the tumor CT image coordinate system based on the diameter parameter and spacing parameter of the lattice target area, and obtains a three-dimensional coordinate matrix of the sphere center; A lattice target area optimization module performs nested iterative optimization on the sphere center three-dimensional coordinate matrix based on translation operators and rotation operators, and uses the number of lattice target area distributions contained in the indented boundary as an optimization evaluation criterion to obtain the optimal result; The optimization result output module generates the corresponding lattice target area outline based on the optimal result.

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