Particle dose determination method and device, equipment and storage medium

Abstract

The invention provides a particle dose determination method and device, equipment and a medium, and is applied to the field of radiation medical treatment and image processing. The particle dose determination method comprises the steps that a first CT image and a second CT image of a to-be-detected tissue are obtained, the energy of first scanning rays corresponding to the first CT image is smaller than the energy of second scanning rays corresponding to the second CT image, the to-be-detected tissue comprises multiple to-be-detected objects, and the first CT image comprises first CT values of the multiple to-be-detected objects; based on the first CT image and the second CT image, determining respective element density of the plurality of to-be-detected objects; on the basis of the number of the to-be-measured objects with the same first CT value in the first CT image and the second CT image, the first CT values of the to-be-measured objects are adjusted, and target CT values of the to-be-measured objects are obtained; and based on the respective target CT values and element densities of the plurality of objects to be detected, simulating the Monte Carlo transport of the particles in the tissue to be detected to obtain the Monte Carlo dosage of the particles.

Description

Technical Field

[0001] The present disclosure relates to the fields of physics and computers, specifically to the application of physics and computer technology in the field of radiation medicine, and more specifically to a particle dose determination method, device, equipment, medium and program product. Background Art

[0002] Computed Tomography (CT) imaging technology is widely used in the field of medical diagnosis. CT imaging technology and image reconstruction technology can present the internal structure of the detected object.

[0003] In the field of radiotherapy, the element density information of the material is calculated through CT images, and the reaction process of particles in the material and the transport and energy deposition of particles in the medium can be simulated based on the Monte Carlo method, so as to determine the effect of radiotherapy. Summary of the invention

[0004] In view of the above problems, the present disclosure provides a particle dose determination method, apparatus, device, medium and program product that improves computational efficiency.

[0005] According to a first aspect of the present disclosure, a method for determining a particle dose is provided, comprising: acquiring a first CT image and a second CT image of a tissue to be tested, the energy of a first scanning ray corresponding to the first CT image being less than the energy of a second scanning ray corresponding to the second CT image, the tissue to be tested comprising a plurality of objects to be tested, the first CT image comprising respective first CT values ​​of the plurality of objects to be tested; determining the elemental density of the plurality of objects to be tested based on the first CT image and the second CT image; adjusting the first CT values ​​of the plurality of objects to be tested based on the number of objects to be tested having the same first CT value in the first CT image and the second CT image to obtain target CT values ​​of the plurality of objects to be tested; and simulating Monte Carlo transport of particles in the tissue to be tested based on the target CT values ​​and elemental densities of the plurality of objects to be tested to obtain the Monte Carlo dose of the particles.

[0006] A second aspect of the present disclosure provides a device for determining a particle dose, comprising: an acquisition module, used to acquire a first CT image and a second CT image of a tissue to be tested, the energy of a first scanning ray corresponding to the first CT image is less than the energy of a second scanning ray corresponding to the second CT image, the tissue to be tested includes a plurality of objects to be tested, and the first CT image includes first CT values ​​of the plurality of objects to be tested respectively; a determination module, used to determine element densities of the plurality of objects to be tested respectively based on the first CT image and the second CT image; an adjustment module, used to adjust the first CT values ​​of the plurality of objects to be tested respectively based on the number of objects to be tested having the same first CT value in the first CT image and the second CT image, to obtain target CT values ​​of the plurality of objects to be tested respectively; and a simulation module, used to simulate Monte Carlo transport of particles in the tissue to be tested based on the target CT values ​​and element densities of the plurality of objects to be tested respectively, to obtain Monte Carlo doses of the particles.

[0007] A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned particle dose determination method.

[0008] A fourth aspect of the present disclosure further provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above-mentioned particle dose determination method.

[0009] The fifth aspect of the present disclosure further provides a computer program product, including a computer program, which implements the above-mentioned particle dose determination method when executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The above contents and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0011] Figure 1 The application scenario diagram of the method for determining the particle dose according to the embodiment of the present disclosure is schematically shown;

[0012] Figure 2 A flow chart schematically shows a method for determining a particle dose according to an embodiment of the present disclosure;

[0013] Figure 3 A schematic diagram of determining a target CT value according to an embodiment of the present disclosure is schematically shown;

[0014] Figure 4 A block diagram schematically shows a structure of a device for determining a particle dose according to an embodiment of the present disclosure; and

[0015] Figure 5 A block diagram of an electronic device suitable for implementing a method for determining a particle dose according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0016] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0017] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0018] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0019] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0020] In the technical solutions disclosed in this disclosure, the collection, storage, use, processing, transmission, provision, disclosure and application of user personal information involved are in compliance with the relevant laws and regulations, necessary confidentiality measures are taken, and they do not violate public order and good morals. In the technical solutions disclosed in this disclosure, the user's authorization or consent is obtained before obtaining or collecting user personal information.

[0021] Figure 1 The application scenario diagram of the particle dose determination method according to an embodiment of the present disclosure is schematically shown.

[0022] The basic physical principle of radiotherapy technology is to irradiate tumor tissue with radiation, and through the interaction between radiation and tissue, deposit the energy it carries into cancer cells to kill them. Its fundamental goal is to kill as many cancer cells as possible (give tumor tissue the highest possible radiation dose) while protecting healthy tissue (give healthy tissue the lowest possible radiation dose).

[0023] Proton radiotherapy is an emerging radiotherapy technology. Compared with traditional X-ray / electron beam radiotherapy, the proton dose curve has a sudden dose peak (Bragg peak). The proton dose is higher and sharper, which can greatly improve the killing efficiency of tumor tissue while achieving lower tissue damage. Compared with photons, proton radiotherapy has lower dose side effects.

[0024] like Figure 1 As shown, the tissue to be treated is modeled to generate a simulated tissue 110 with particle deposition. The simulated particle flow 120 is incident from a specified position of the simulated tissue 110 and deposited at different positions of the simulated tissue 110. The particle dose determination method provided by the embodiment of the present disclosure is used to calculate the dose of the particle source 120 in the simulated tissue 110.

[0025] The simulated tissue 110 of the tissue to be tested is constructed using the CT image of the tissue to be tested. The CT image of the tissue to be tested can describe the HU value distribution of the tissue to be tested, and the HU value reflects the interaction between matter and photons.

[0026] However, the X-ray source of traditional CT equipment can only emit scanning rays with one energy spectrum, that is, single-energy CT. When multiple tissue materials are scanned based on a single ray source, the elemental components of the multiple tissue materials are different but the HU values ​​under a single energy spectrum may be the same. In this case, the two tissue materials cannot be further distinguished in the CT image, which leads to deviations in the diagnosis results.

[0027] For example, a dual-energy CT device has two energy spectra. Different energy spectra can be formed based on different radiation sources, and the energy components included in multiple energy spectra can be different. When a CT device scans the same tissue material based on different energy spectra, the HU values ​​may be the same or different.

[0028] Therefore, using dual-energy CT, two CT images of two tissue materials scanned based on two energy spectra can be compared. When the HU values ​​of two tissue materials are the same under one energy spectrum, the HU values ​​under another energy spectrum are often different, thereby further distinguishing the two tissue materials.

[0029] Since the particle transport process in the human body is very complex, it needs to be realized through the Monte Carlo simulation method. Common Monte Carlo simulation software includes FLUKA and Geant4. Monte Carlo simulation software can calculate the dose distribution of particles (photons, protons and heavy ions) based on the element density distribution in tissue materials. However, due to different logical structures, Monte Carlo simulation software can usually only read single-energy CT, which makes it impossible to directly apply dual-energy CT images to Monte Carlo simulation software.

[0030] Since the Monte Carlo simulation software can only read the CT images of single-energy CT, when the HU values ​​of two materials are the same under the single-energy CT images, the Monte Carlo simulation software cannot distinguish the two materials, resulting in deviations in the simulated particle transport process. In addition, the Monte Carlo simulation software cannot read the element density distribution calculated based on dual-energy CT, so the current Monte Carlo simulation software cannot give full play to the advantages of dual-energy CT element analysis.

[0031] Based on this, the present disclosure provides a method for determining a particle dose, which utilizes a dual-energy CT image of a tissue to be tested to simulate the Monte Carlo transport of particles in the tissue to be tested, so as to calculate the Monte Carlo dose of the particles.

[0032] Figure 2 The flowchart of the method for determining the particle dose according to the embodiment of the present disclosure is schematically shown.

[0033] like Figure 2 As shown, the particle dose determination method of this embodiment includes operations S201 to S204.

[0034] In operation S210 , a first CT image and a second CT image of a tissue to be tested are acquired.

[0035] In the embodiment of the present disclosure, the first CT image may be obtained by scanning the tissue to be tested based on the first scanning ray by the CT device, and the second CT image may be obtained by scanning the tissue to be tested based on the second scanning ray by the CT device. The energy of the first scanning ray corresponding to the first CT image is less than the energy of the second scanning ray corresponding to the second CT image. Therefore, the first CT image may be a low-energy CT image, and the second CT image may be a high-energy CT image.

[0036] In the disclosed embodiment, the tissue to be tested includes a plurality of objects to be tested, the first CT image includes the first CT values ​​of the plurality of objects to be tested, and the second CT image includes the second CT values ​​of the plurality of objects to be tested. The tissue to be tested represented by the first CT image and the second CT image can be considered to be composed of a plurality of voxel blocks, and each voxel can be represented as an object to be tested. For example, the tissue to be tested can be a tumor area. The CT value is a HU (Hounsfield Unit) value used to represent a voxel. The HU value is a unit of measurement for determining the density of a local tissue or organ, and can reflect the degree of absorption of X-rays by the tissue or organ.

[0037] In operation S220 , element densities of the respective plurality of objects to be tested are determined based on the first CT image and the second CT image.

[0038] In the embodiment of the present disclosure, based on the distribution law between the dual-energy CT value and the element density of the dual-energy CT, the element density of each object to be tested can be determined based on the dual-energy CT value of each object to be tested. The distribution law between the dual-energy CT value and the element density can be obtained based on the known dual-energy CT value and element density of the sample material.

[0039] For example, the known dual-energy CT value and element density of the sample material are fitted to obtain a fitting function that describes the distribution law. The fitting function describes the distribution law between the dual-energy CT value and the element density. When the dual-energy CT value and the fitting function of the object to be tested are known, the element density of the object to be tested can be calculated.

[0040] For example, the known dual-energy CT value and element density of the sample material are input into the deep model, and the deep model is used to learn the data features of the dual-energy CT value, the data features of the element density, and the correlation features between the dual-energy CT value and the element density, so as to realize model training. The trained deep model learns the distribution law between the dual-energy CT value and the element density. The dual-energy CT value of the object to be tested is input into the trained deep model, and the deep model can output the element density of the object to be tested.

[0041] The element density of the object to be tested may include the density of carbon, nitrogen, oxygen, hydrogen, calcium, and phosphorus elements of the object to be tested. Based on the first dual-energy CT image and the second CT image, the density distribution of each element in the tissue to be tested can be obtained. The density distribution of each element can be represented by a three-dimensional matrix, and each value in the three-dimensional matrix can represent the element density of an object to be tested.

[0042] In operation S230, based on the number of objects having the same first CT value in the first CT image and the second CT image, the first CT values ​​of the plurality of objects are adjusted to obtain target CT values ​​of the plurality of objects, and the plurality of target CT values ​​are different from each other.

[0043] In a dual-energy CT image, different objects to be tested may have the same first CT value and different second CT values. Therefore, if there is a corresponding relationship between the first CT value and the second CT value of the same object to be tested, there may be a corresponding relationship between one first CT value and multiple second CT values.

[0044] The CT value of the low-energy CT image has a large span, so based on the first CT image, according to the number of objects to be tested with the same first CT value in the first CT image and the second CT image, the first CT value of each object to be tested in the first CT image is reassigned to obtain the target CT value of each object to be tested. The target CT values ​​of each object to be tested are different from each other, and the target CT values ​​of each object to be tested constitute the target CT image of the tissue to be tested.

[0045] In the embodiment of the present disclosure, the first CT values ​​of the respective objects to be tested are assigned based on their respective second CT values, and the difference between the second CT values ​​of the plurality of objects to be tested can be fully utilized. The first CT values ​​of the respective objects to be tested are assigned based on the number of objects to be tested having the same first CT value in the first CT image, and the range of the assigned values ​​can be determined.

[0046] In operation S240 , based on the target CT values ​​and element densities of the multiple objects to be tested, Monte Carlo transport of particles in the tissue to be tested is simulated to obtain Monte Carlo doses of the particles.

[0047] For example, particles can be protons, photons, heavy ions, etc. The transport of particles is simulated by Monte Carlo simulation software. For example, the transport of particles can be simulated by Monte Carlo simulation software such as Geant4, Gate, Fluka, Topas, etc. By establishing a matrix model for the tissue to be tested, the matrix model includes the position coordinate information, element information and voxel density information (converted from HU value) of the voxel block, which can characterize the transport process of particles and determine the position information and energy information of particles.

[0048] In the embodiment of the present disclosure, the first CT image and the second CT image are converted into a target CT image, thereby realizing the conversion from dual-energy CT to single-energy CT. In the target CT image, the target CT values ​​of the objects to be tested are different from each other, so the objects to be tested with different element densities can be clearly distinguished based on the target CT values.

[0049] Since the adjustment method of the first CT image is related to the number of objects to be tested having the same first CT value in the first CT image and the second CT image, the adjustment methods of multiple tissues to be tested may be different, and the target CT images of multiple tissues to be tested are also different.

[0050] After converting the first CT image and the second CT image into a target CT image, the Monte Carlo simulation software can read the target CT image. In addition, since the target CT images of multiple tissues to be tested are different from each other, the Monte Carlo simulation conversion can simulate different materials based on the target CT image, thereby distinguishing tissues to be tested with different components.

[0051] Through the implementation of the present disclosure, a dual-energy CT image that can distinguish different elemental components is converted into a single-energy CT image, and the CT value characteristics of the dual-energy CT image are retained in the converted single-energy CT image. Based on the single-energy CT images obtained by converting multiple tissues to be tested, the Monte Carlo simulation software can assign different types of materials to the multiple tissues to be tested, and associate different types of materials with their respective elemental densities, thereby obtaining simulated tissues of the multiple tissues to be tested. By counting the Monte Carlo dose of particles based on the target CT image obtained by conversion, the accuracy of dual-energy CT in describing the tissues to be tested can be fully utilized. Based on the first CT image, the first image is reassigned according to the second CT image, and the characteristic of the large span of the CT value range in the first CT image can be retained to improve the accuracy of the target CT image.

[0052] Figure 3 A schematic diagram of determining a target CT value according to an embodiment of the present disclosure is schematically shown.

[0053] like Figure 3 As shown, based on the first CT values ​​of all the objects to be tested of the tissue to be tested in the first CT image 310, the objects to be tested are divided into first objects to be tested 311 and second objects to be tested 312. For any first object to be tested 311, there is at least one object to be tested among all the objects to be tested that has the same first CT value as the first object to be tested 311. For any second object to be tested 312, the first CT values ​​of all the objects to be tested are different from the first CT value of the second object to be tested.

[0054] In the embodiment of the present disclosure, the adjustment amplitude 330 is determined based on the number of first objects to be tested 311 in the first CT image 310. For the plurality of first objects to be tested 331, the first CT values ​​of the plurality of first objects to be tested 311 are adjusted based on the adjustment amplitude 330 and the second CT values ​​of the plurality of first objects to be tested 311 in the second CT image 320, and the target CT values ​​340 of the plurality of first objects to be tested are obtained. For the plurality of second objects to be tested 312, the first CT values ​​of the plurality of second objects to be tested 312 are adjusted based on the adjustment amplitude 330, and the target CT values ​​340 of the plurality of second objects to be tested 312 are obtained.

[0055] In the disclosed embodiment, the adjustment amplitude 330 may be positively correlated with the number of first test objects 311. When the number of first test objects 311 is large, the first CT value needs to be adjusted by a larger amplitude so that the first CT value can be reassigned within a sufficient value range.

[0056] For the first object to be tested 311, the first CT value of the first object to be tested 311 is reassigned according to the second CT value of the first object to be tested 311. When the first CT values ​​of the two first objects to be tested 311 are the same and the second CT values ​​are similar, the elemental composition of the two first objects to be tested is similar, so the difference in the value assigned to the two first objects to be tested 311 is small. When the first CT values ​​of the two first objects to be tested 311 are the same and the second CT values ​​are greatly different, the elemental composition of the two first objects to be tested is also greatly different, so the difference in the value assigned to the two first objects to be tested 311 is large.

[0057] In the disclosed embodiment, the first CT values ​​of the first objects to be tested 311 are assigned in sequence with reference to the numerical values ​​of the second CT values ​​of the plurality of first objects to be tested 311, so that the numerical value relationship between the target CT values ​​of the first objects to be tested 311 is similar to the numerical value relationship between the second CT values.

[0058] For the second object to be tested 312, since the first CT values ​​of the plurality of second objects to be tested 312 are different from each other, in order to unify the span range of the target CT values ​​of the first object to be tested 311 and the second object to be tested 312, the first CT value of the second object to be tested 312 is adjusted with the same adjustment amplitude 330. The target CT values ​​of the second objects to be tested 312 after the amplitude adjustment are also different from each other, so there is no need to refer to the second CT value of the second object to be tested 312 for reassignment.

[0059] In the embodiment of the present disclosure, the value of the adjustment amplitude 330 may be determined based on the number of the first CT values ​​of the first object to be tested 311 .

[0060] For example, among the multiple first test objects 311, the first CT values ​​of the first test objects 311 are not necessarily completely the same. For example, there may be at least one first CT value corresponding to the multiple first test objects.

[0061] For example, based on the first CT image, the number of objects to be tested corresponding to each first CT value is determined. If it is determined that there are multiple objects to be tested corresponding to multiple first CT values, the maximum number of objects to be tested corresponding to the multiple first CT values ​​is used as the adjustment range.

[0062] For example, among the plurality of first objects to be tested 311, there are M first objects to be tested 311 whose first CT values ​​are all 1000, there are N first objects to be tested 311 whose first CT values ​​are all 900, and there are Q first objects to be tested 311 whose first CT values ​​are all 800. When M is the maximum value among M, N and Q, M is used as the adjustment amplitude 330.

[0063] When there are multiple first CT values ​​corresponding to multiple objects to be tested (there are multiple "one-to-many" situations), the maximum value among the number of objects to be tested is used as the adjustment range to meet the required assignment range of the multiple "one-to-many" situations. For the situation where the number of objects to be tested corresponding to the first CT value is the largest, the required assignment range of the first CT value is the largest. Since the number of objects to be tested in other "one-to-many" situations is less than or equal to the maximum value, the assignment range of the first CT value in other "one-to-many" situations is less than or equal to the assignment range required for the first CT value with the largest number of objects to be tested. When the assignment range requirements of the first CT value with the largest number of objects to be tested can be met, the assignment range requirements of other "one-to-many" situations can all be met.

[0064] In the embodiment of the present disclosure, the adjustment method for the first CT value of the first object to be tested 311 may include: based on the adjustment amplitude, multiplying the first CT value of each of the multiple first objects to be tested 311 to obtain the multiplied value of each of the multiple first objects to be tested 311; sorting the second CT values ​​of each of the multiple first objects to be tested 311 with the same first CT value in ascending order to obtain at least one ascending sequence; and based on the at least one ascending sequence, assigning the multiplied value of each of the multiple first objects to be tested 311 with the same first CT value in turn to obtain the target CT value of each of the multiple first objects to be tested 311.

[0065] A plurality of first test objects having the same first CT value may be defined as an object group. The first CT value of the first test object in each object group is multiplied based on the adjustment amplitude. Then, based on the ascending order of the second CT values ​​of the first test objects in each object group, the multiplied values ​​are assigned in sequence from small to large, so that the ascending order of the target CT values ​​of the plurality of first test objects is consistent with the ascending order of the corresponding plurality of second CT values.

[0066] For example, the first CT values ​​of the four first objects to be tested in the first object group are all 900, and the second CT values ​​are 810, 820, 830 and 850 respectively; the first CT values ​​of the five first objects to be tested in the second object group are all 1000, and the second CT values ​​are 900, 920, 930, 940 and 950 respectively, and the adjustment amplitude is 5. Then, the first CT value of the first object to be tested in the first object group is doubled to 4500, and the first CT value of the first object to be tested in the second object group is doubled to 4000.

[0067] According to the order of the second CT values ​​of the four first objects to be tested in the first object group, the multiplied value of the first object to be tested whose second CT value is 810 is assigned a multiplied value of 4500, the multiplied value of the first object to be tested whose second CT value is 820 is assigned a multiplied value of 4501, the multiplied value of the first object to be tested whose second CT value is 830 is assigned a multiplied value of 4502, and the multiplied value of the first object to be tested whose second CT value is 850 is assigned a multiplied value of 4503.

[0068] According to the ascending order of the second CT values ​​of the five first objects to be tested in the second object group, the multiplied value of the first object to be tested whose second CT value is 900 is assigned a multiplied value of 5000, the multiplied value of the first object to be tested whose second CT value is 920 is assigned a multiplied value of 5001, the multiplied value of the first object to be tested whose second CT value is 930 is assigned a multiplied value of 5002, the multiplied value of the first object to be tested whose second CT value is 940 is assigned a multiplied value of 5003, and the multiplied value of the first object to be tested whose second CT value is 950 is assigned a multiplied value of 5004.

[0069] That is, the target CT values ​​of the four first objects to be tested in the first object group are 4500, 4501, 4502 and 4503. The target CT values ​​of the five first objects to be tested in the second object group are 5000, 5001, 5002, 5003 and 5004 respectively.

[0070] For the second objects to be tested, when the first CT values ​​of the plurality of second objects to be tested are 899, 901, 999 and 1001 respectively, the target CT values ​​of the plurality of second objects to be tested are 4495, 4505, 4995 and 5005 respectively.

[0071] In the disclosed embodiment, after the first CT values ​​of all the objects to be tested in the tissue to be tested are reassigned, the target CT values ​​of all the objects to be tested are obtained. The target CT values ​​of all the objects to be tested are not equal to each other. The assignment method is related to the number of the same first CT values ​​and the second CT value in the tissue to be tested, so the assignment method of each tissue to be tested is different, and the target CT images obtained by the assignment are also different.

[0072] In an embodiment of the present disclosure, when the number of first objects to be tested included in the object group is too large, the object group can be divided into multiple material groups, each material group including multiple first objects to be tested, and the multiple first objects to be tested included in each material group are regarded as an independent object, and the multiple first objects to be tested included in each material group are assigned values, so that the target CT values ​​of the multiple first objects to be tested included in each material group are the same.

[0073] In the embodiment of the present disclosure, when the number of first objects to be tested included in the object group is too large, the method of adjusting the first CT value of the first object to be tested 311 may include: sorting the second CT values ​​of each of the multiple first objects to be tested in the object group in ascending order to obtain at least one ascending sequence; based on the at least one ascending sequence, dividing the multiple first objects to be tested in the object group into multiple material groups; based on the adjustment amplitude, multiplying the first CT values ​​of the multiple material groups to obtain the multiplied values ​​of the multiple material groups; and assigning the multiplied values ​​of the multiple material groups in turn to obtain the target CT values ​​of the multiple first objects to be tested, wherein the target CT values ​​of the multiple first objects to be tested included in each material group are the same.

[0074] Based on the ascending order of the second CT values ​​of the first objects to be tested in each object group, each object group including a plurality of first objects to be tested is divided into a plurality of material groups, and the number of first objects to be tested included in each material group may be the same. For example, referring to the ascending order of the second CT values, every three first objects to be tested in the object group are divided into one material group.

[0075] The adjustment range may be determined based on the number of material groups in each object group. For example, the adjustment range may be consistent with the maximum number of material groups in the plurality of object groups.

[0076] For example, for multiple object groups, multiple material groups can be divided into multiple material groups with the same granularity, and the number of first objects to be tested included in the divided material groups is the same. In this case, the maximum number of material groups in the multiple object groups is used as the adjustment amplitude. For example, the multiple object groups are divided into 5 material groups, 4 material groups and 3 material groups, respectively, and each material group includes 4 first objects to be tested. In this case, the adjustment amplitude is 5.

[0077] For example, multiple object groups can be divided into the same number of material groups, and the number of first objects to be tested included in each material group may be different or the same. In this case, the number of material groups into which each object group is divided is used as the adjustment range. For example, multiple object groups are divided into 4 material groups, and the material groups of each of the multiple object groups can include 3, 4, and 5 first objects to be tested, respectively. In this case, the adjustment range is 4.

[0078] Based on the second CT value of the first object to be tested in each material group, the multiple material groups can also be sorted from small to large based on the second CT value. Based on the ascending order of the multiple material groups, the first objects to be tested included in the multiple material groups are assigned values ​​from small to large in sequence, so that the ascending order of the target CT values ​​of the first objects to be tested included in the multiple material groups is consistent with the ascending order of the multiple material groups.

[0079] In the disclosed embodiments, the conversion relationship between CT value and element density is determined based on the target CT value and element density of each of the multiple objects to be tested; based on the target CT value and the conversion relationship, the simulated tissue corresponding to the tissue to be tested is simulated; and in the simulated tissue, the Monte Carlo transport process of the particles is simulated to obtain the Monte Carlo dose of the particles.

[0080] Monte Carlo simulation software can define material types based on element density, and then assign the pre-defined material type corresponding to the CT value to the voxel of the tissue to be tested based on the conversion relationship between CT value and element density.

[0081] The conversion relationship between CT value and element density can describe the conversion relationship between the target CT value and element density of the object to be tested. The Monte Carlo simulation software can pre-learn the conversion relationship between the target CT value and element density, and after reading the target CT value of each object to be tested, assign the corresponding type of material to the object to be tested, so that the Monte Carlo simulation software can simulate the element density of the object to be tested.

[0082] After all the objects to be tested of the tissue to be tested are given the corresponding type of material, the Monte Carlo simulation software simulates the simulated tissue of the tissue to be tested, thereby simulating the element density distribution of the tissue to be tested. Using the element density distribution of the tissue to be tested, the Monte Carlo simulation software can simulate the transport process of particles inside the tissue to be tested, thereby statistically analyzing the particle dose distribution.

[0083] In the embodiment of the present disclosure, when the object group is divided into multiple material groups, the Monte Carlo dose statistics method of the particles may include: determining the average element density of each of the multiple material groups based on the element density of each of the multiple first objects to be tested included in the multiple material groups; and simulating the Monte Carlo transport of particles in the tissue to be tested based on the target CT value of each of the multiple first objects to be tested and the average element density of the material group to which they belong as well as the target CT value and element density of each of the multiple second objects to be tested to obtain the Monte Carlo dose of the particles.

[0084] In the case where the object group is divided into multiple material groups, the target CT values ​​of the multiple first objects to be tested included in the material group are the same. In order to determine the conversion relationship between the target CT value and the element density, it is necessary to uniformly process the element densities of the multiple first objects to be tested included in the material group. For example, the material group including the multiple first objects to be tested is uniformly defined as a new material, the average value of the element density of the multiple first objects to be tested included in the material group is used as the element density of the new material, and the target CT value of the multiple first objects to be tested included in the material group is used as the target CT value of the new material. It can be understood that the material group including the multiple first objects to be tested are all considered to be the same material.

[0085] The particle determination method disclosed in the present invention is schematically described below in conjunction with an embodiment.

[0086] For example, the tissue to be tested has dual-energy CT images of 80 kV and 150 kV, wherein the HU values ​​of voxel 1, voxel 2, voxel 3, and voxel 4 in the 80 kV CT image are all equal to 1000, and the first CT values ​​of voxel 1, voxel 2, voxel 3, and voxel 4 can be recorded as HUL1=HUL2=HUL3=HUL4=1000. In the 150 kV CT image, the HU values ​​of voxel 1, voxel 2, voxel 3, and voxel 4 are HUH1=770, HUH2=780, HUH3=790, and HUH4=800, respectively. Voxel 1, voxel 2, voxel 3, and voxel 4 form an object group.

[0087] To simplify the calculation, voxels 1, 2, 3, and 4 of the object group are equally divided into two material groups based on the HUH values ​​of voxels 1, 2, 3, and 4. According to the order of the second CT values ​​of voxels 1, 2, 3, and 4 from small to large, two voxels are divided into a group, that is, voxels 1 and voxel 2 are divided into material group 1, and voxels 3 and voxel 4 are divided into material group 2.

[0088] Using the dual-energy CT element analysis algorithm, with (1000,770), (1000,780), (1000,790), (1000,800) as input, the element density ρ of voxel 1, voxel 2, voxel 3 and voxel 4 can be obtained (the unit of ρ is g / cm 3 ).

[0089] Voxel 1: ρ(H)1=0.07, ρ(C)1=0.31, ρ(N)1=0.07, ρ(O)1=0.67, ρ(P)1=0.13, ρ(Ca)1=0.31;

[0090] Voxel 2: ρ(H)1=0.06, ρ(C)1=0.3, ρ(N)1=0.07, ρ(O)1=0.68, ρ(P)1=0.14, ρ(Ca)1=0.32;

[0091] Voxel 3: ρ(H)1=0.05, ρ(C)1=0.29, ρ(N)1=0.07, ρ(O)1=0.69, ρ(P)1=0.15, ρ(Ca)1=0.33;

[0092] Voxel 4: ρ(H)1=0.04, ρ(C)1=0.28, ρ(N)1=0.07, ρ(O)1=0.70, ρ(P)1=0.16, ρ(Ca)1=0.34.

[0093] Based on the elemental densities of voxel 1, voxel 2, voxel 3, and voxel 4, the elemental density of each material group can be calculated, namely:

[0094] Material group 1: ρ'(H)1=0.065, ρ'(C)1=0.305, ρ'(N)1=0.07, ρ'(O)1=0.675, ρ'(P)1=0.135, ρ'(Ca)1=0.315;

[0095] Material group 2: ρ'(H)1=0.055, ρ'(C)1=0.285, ρ'(N)1=0.07, ρ'(O)1=0.695, ρ'(P)1=0.155, ρ'(Ca)1=0.335.

[0096] Since the object group is divided into two material groups, the adjustment amplitude may be 2. Based on the adjustment amplitude and the second CT value of the voxel in the material group, the first CT value and the second CT value of each of voxel 1, voxel 2, voxel 3 and voxel 4 are converted into a target CT value.

[0097] For example, the sum of the second CT value of voxel 1 and the second CT value of voxel 2 in material group 1 is less than the sum of the second CT value of voxel 3 and the second CT value of voxel 4 in material group 2. Therefore, the target CT of material group 1 may be 2+1000+0=2000, and the target CT value of material group 2 may be 2+1000+1=2001.

[0098] In the Monte Carlo simulation software, voxel points with a HU value of 2000 are assigned to voxel 1 and voxel 2, and voxel points with a HU value of 2001 are assigned to voxel 3 and voxel 4. The Monte Carlo simulation software also reads the conversion relationship between the target CT value and the element density of each of material group 1 and material group 2 to obtain the simulated tissue of the tissue to be tested and simulate the Monte Carlo transport of particles.

[0099] Based on the above-mentioned particle dose determination method, the present disclosure also provides a particle dose determination device. Figure 4 The device is described in detail.

[0100] Figure 4 The structural block diagram of the device for determining particle dose according to an embodiment of the present disclosure is schematically shown.

[0101] like Figure 4 As shown, the particle dose determination device 400 of this embodiment includes an acquisition module 410 , a determination module 420 , an adjustment module 430 and a simulation module 440 .

[0102] The acquisition module 410 is used to acquire a first CT image and a second CT image of the tissue to be tested, the energy of the first scanning ray corresponding to the first CT image is less than the energy of the second scanning ray corresponding to the second CT image, the tissue to be tested includes a plurality of objects to be tested, and the first CT image includes first CT values ​​of the plurality of objects to be tested. In one embodiment, the acquisition module 410 can be used to perform the operation S201 described above, which will not be described in detail herein.

[0103] The determination module 420 is used to determine the element density of each of the plurality of objects to be tested based on the first CT image and the second CT image. In one embodiment, the determination module 420 can be used to perform the operation S202 described above, which will not be described in detail herein.

[0104] The adjustment module 430 is used to adjust the first CT values ​​of the plurality of objects to be tested based on the number of objects to be tested having the same first CT value in the first CT image and the second CT image to obtain the target CT values ​​of the plurality of objects to be tested. In one embodiment, the adjustment module 430 can be used to perform the operation S203 described above, which will not be described in detail here.

[0105] The simulation module 440 is used to simulate the Monte Carlo transport of particles in the tissue to be tested based on the target CT values ​​and element densities of the multiple objects to be tested, and obtain the Monte Carlo dose of the particles. In one embodiment, the simulation module 440 can be used to perform the operation S204 described above, which will not be repeated here.

[0106] According to an embodiment of the present disclosure, the adjustment module 430 is also used to determine an adjustment amplitude based on the number of objects to be tested having the same first CT value in the first CT image; for multiple first objects to be tested having the same first CT value, based on the adjustment amplitude and the second CT values ​​of the multiple first objects to be tested in the second CT image, adjust the first CT values ​​of the multiple first objects to be tested to obtain target CT values ​​of the multiple first objects to be tested; and for multiple second objects to be tested having different first CT values, based on the adjustment amplitude, adjust the first CT values ​​of the multiple second objects to be tested to obtain target CT values ​​of the multiple second objects to be tested.

[0107] According to an embodiment of the present disclosure, the adjustment module 430 is further used to determine the number of objects to be tested corresponding to each first CT value based on the first CT image; and to use the maximum value of the number of objects to be tested corresponding to each first CT value as the adjustment amplitude.

[0108] According to an embodiment of the present disclosure, the adjustment module 430 is further configured to multiply the first CT value of each of the plurality of first objects to be tested based on the adjustment amplitude to obtain the multiplied value of each of the plurality of first objects to be tested;

[0109] sorting the second CT values ​​of the plurality of first test objects having the same first CT value in ascending order to obtain at least one ascending sequence; and

[0110] Based on at least one ascending sequence, the multiplication values ​​of the plurality of first objects to be tested having the same first CT value are assigned in sequence to obtain the target CT values ​​of the plurality of first objects to be tested.

[0111] According to an embodiment of the present disclosure, the adjustment module 430 is also used to sort the second CT values ​​of each of the multiple first objects to be tested having the same first CT value in ascending order to obtain at least one ascending sequence; based on the at least one ascending sequence, the multiple first objects to be tested having the same first CT value are divided into multiple material groups; based on the adjustment amplitude, the first CT values ​​of the multiple material groups are multiplied to obtain the multiplied values ​​of the multiple material groups; and the multiplied values ​​of the multiple material groups are assigned in turn to obtain the target CT values ​​of the multiple first objects to be tested, wherein the target CT values ​​of the multiple first objects to be tested included in each material group are the same.

[0112] According to an embodiment of the present disclosure, the simulation module 440 is also used to determine the average elemental density of each of the multiple material groups based on the elemental density of each of the multiple first objects to be tested included in the multiple material groups; and to simulate the Monte Carlo transport of particles in the tissue to be tested based on the target CT value of each of the multiple first objects to be tested and the average elemental density of the material group to which they belong, as well as the target CT value and elemental density of each of the multiple second objects to be tested, so as to obtain the Monte Carlo dose of the particles.

[0113] According to an embodiment of the present disclosure, the simulation module 440 is also used to determine the conversion relationship between CT value and element density based on the target CT value and element density of each of the multiple objects to be tested; based on the target CT value and the conversion relationship, simulate the simulated tissue corresponding to the tissue to be tested; and in the simulated tissue, simulate the Monte Carlo transport process of particles to obtain the Monte Carlo dose of the particles.

[0114] According to an embodiment of the present disclosure, any multiple modules among the acquisition module 410, the determination module 420, the adjustment module 430 and the simulation module 440 can be combined into one module for implementation, or any one of the modules can be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules can be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the acquisition module 410, the determination module 420, the adjustment module 430 and the simulation module 440 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation modes of software, hardware and firmware or in a proper combination of any of them. Alternatively, at least one of the acquisition module 410, the determination module 420, the adjustment module 430 and the simulation module 440 can be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding function can be performed.

[0115] Figure 5 A block diagram of an electronic device suitable for implementing a method for determining a particle dose according to an embodiment of the present disclosure is schematically shown.

[0116] like Figure 5 As shown, the electronic device 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage part 508 to a random access memory (RAM) 503. The processor 501 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 501 may also include an onboard memory for caching purposes. The processor 501 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0117] In RAM 503, various programs and data required for the operation of electronic device 500 are stored. Processor 501, ROM 502 and RAM 503 are connected to each other via bus 504. Processor 501 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 502 and / or RAM 503. It should be noted that the program can also be stored in one or more memories other than ROM 502 and RAM 503. Processor 501 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in one or more memories.

[0118] According to an embodiment of the present disclosure, the electronic device 500 may further include an input / output (I / O) interface 505, which is also connected to the bus 504. The electronic device 500 may further include one or more of the following components connected to the I / O interface 505: an input portion 506 including a keyboard, a mouse, etc.; an output portion 507 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 508 including a hard disk, etc.; and a communication portion 509 including a network interface card such as a LAN card, a modem, etc. The communication portion 509 performs communication processing via a network such as the Internet. A drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 510 as needed, so that a computer program read therefrom is installed into the storage portion 508 as needed.

[0119] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0120] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, it may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, an apparatus or a device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 502 and / or RAM 503 described above and / or one or more memories other than ROM 502 and RAM 503.

[0121] The embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the particle dose determination method provided by the embodiment of the present disclosure.

[0122] The above functions defined in the system / device of the embodiment of the present disclosure are performed when the computer program is executed by the processor 501. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0123] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 509, and / or installed from the removable medium 511. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0124] In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 509, and / or installed from the removable medium 511. When the computer program is executed by the processor 501, the above functions defined in the system of the embodiment of the present disclosure are performed. According to the embodiment of the present disclosure, the system, device, means, module, unit, etc. described above can be implemented by a computer program module.

[0125] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0126] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0127] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways, even if such combinations and / or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways without departing from the spirit and teachings of the present disclosure. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0128] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for determining a particle dose, comprising: Acquire a first CT image and a second CT image of a tissue to be tested, wherein the energy of a first scanning ray corresponding to the first CT image is less than the energy of a second scanning ray corresponding to the second CT image, the tissue to be tested includes a plurality of objects to be tested, and the first CT image includes first CT values ​​of the plurality of objects to be tested; Determining element density of each of the plurality of objects to be tested based on the first CT image and the second CT image; Based on the number of objects to be tested having the same first CT value in the first CT image and the second CT image, adjusting the first CT values ​​of the plurality of objects to be tested to obtain target CT values ​​of the plurality of objects to be tested; as well as Based on the target CT values ​​and the element densities of the multiple objects to be tested, the Monte Carlo transport of particles in the tissue to be tested is simulated to obtain the Monte Carlo dose of the particles.

2. The determination method according to claim 1, wherein: The adjusting the first CT values ​​of the plurality of objects to be tested based on the number of objects to be tested having the same first CT value in the first CT image and the second CT image to obtain the target CT values ​​of the plurality of objects to be tested comprises: determining an adjustment amplitude based on the number of objects to be tested having the same first CT value in the first CT image; For a plurality of first objects to be tested having the same first CT value, adjusting the first CT value of each of the plurality of first objects to be tested based on the adjustment amplitude and the second CT value of each of the plurality of first objects to be tested in the second CT image to obtain a target CT value of each of the plurality of first objects to be tested; and For a plurality of second objects to be tested having different first CT values, the first CT values ​​of the plurality of second objects to be tested are adjusted based on the adjustment amplitude to obtain target CT values ​​of the plurality of second objects to be tested.

3. The determination method according to claim 2, wherein: The step of determining the adjustment range based on the number of the objects to be tested having the same first CT value in the first CT image includes: Based on the first CT image, determining the number of objects to be tested corresponding to each first CT value; and The maximum value of the number of objects to be tested corresponding to each first CT value is used as the adjustment amplitude.

4. The determination method according to claim 2, wherein: The adjusting the first CT values ​​of the plurality of first objects to be tested based on the adjustment amplitude and the second CT values ​​of the plurality of first objects to be tested in the second CT image to obtain the target CT values ​​of the plurality of first objects to be tested comprises: Based on the adjustment amplitude, the first CT value of each of the plurality of first objects to be tested is multiplied to obtain a multiplied value of each of the plurality of first objects to be tested; sorting the second CT values ​​of the plurality of first test objects having the same first CT value in ascending order to obtain at least one ascending sequence; and Based on the at least one ascending sequence, the multiplication values ​​of the plurality of first objects to be tested having the same first CT value are assigned in sequence to obtain the target CT values ​​of the plurality of first objects to be tested.

5. The determination method according to claim 2, wherein: The adjusting the first CT values ​​of the plurality of first objects to be tested based on the adjustment amplitude and the second CT values ​​of the plurality of first objects to be tested in the second CT image to obtain the target CT values ​​of the plurality of first objects to be tested comprises: sorting the second CT values ​​of the plurality of first test objects having the same first CT value in ascending order to obtain at least one ascending sequence; Based on the at least one ascending sequence, dividing the plurality of first objects to be tested having the same first CT value into a plurality of material groups; Based on the adjustment amplitude, multiplying the first CT values ​​of the plurality of material groups to obtain respective multiplied values ​​of the plurality of material groups; and The multiplication values ​​of the plurality of material groups are assigned in sequence to obtain the target CT values ​​of the plurality of first objects to be tested, wherein the target CT values ​​of the plurality of first objects to be tested included in each of the material groups are the same.

6. The determination method according to claim 5, wherein: The step of simulating the Monte Carlo transport of particles in the tissue to be tested based on the target CT values ​​and the element densities of the multiple objects to be tested to obtain the Monte Carlo dose of the particles includes: Determining an average element density of each of the plurality of material groups based on the element density of each of the plurality of first objects to be measured included in the plurality of material groups; and Based on the target CT values ​​of each of the multiple first objects to be tested and the average element density of the material group to which they belong, and the target CT values ​​and element density of each of the multiple second objects to be tested, Monte Carlo transport of particles in the test tissue is simulated to obtain a Monte Carlo dose of the particles.

7. The determination method according to claim 1, wherein: The step of simulating the Monte Carlo transport of particles in the tissue to be tested based on the target CT values ​​and the element densities of the multiple objects to be tested to obtain the Monte Carlo dose of the particles includes: Determining a conversion relationship between CT value and element density based on the target CT values ​​of the plurality of objects to be tested and the element density; Based on the target CT value and the conversion relationship, simulating a simulated tissue corresponding to the tissue to be tested; and In the simulated tissue, the Monte Carlo transport process of the particles is simulated to obtain the Monte Carlo dose of the particles.

8. A device for determining a particle dose, comprising: an acquisition module, configured to acquire a first CT image and a second CT image of a tissue to be tested, wherein the energy of a first scanning ray corresponding to the first CT image is less than the energy of a second scanning ray corresponding to the second CT image, the tissue to be tested includes a plurality of objects to be tested, and the first CT image includes first CT values ​​of the plurality of objects to be tested; A determination module, configured to determine element densities of each of the plurality of objects to be tested based on the first CT image and the second CT image; an adjustment module, configured to adjust the first CT values ​​of the plurality of objects to be tested based on the number of objects to be tested having the same first CT value in the first CT image and the second CT image, so as to obtain target CT values ​​of the plurality of objects to be tested; as well as The simulation module is used to simulate the Monte Carlo transport of particles in the tissue to be tested based on the target CT value and the element density of each of the multiple objects to be tested, so as to obtain the Monte Carlo dose of the particles.

9. An electronic device, comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 7.

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