CN111494815B - Three-dimensional dose calculation method, device and medium based on mixed variable-scale model - Google Patents
Three-dimensional dose calculation method, device and medium based on mixed variable-scale model Download PDFInfo
- Publication number
- CN111494815B CN111494815B CN202010407021.0A CN202010407021A CN111494815B CN 111494815 B CN111494815 B CN 111494815B CN 202010407021 A CN202010407021 A CN 202010407021A CN 111494815 B CN111494815 B CN 111494815B
- Authority
- CN
- China
- Prior art keywords
- scale
- variable
- calculation
- dose
- scale model
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/103—Treatment planning systems
- A61N5/1031—Treatment planning systems using a specific method of dose optimization
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
- A61N5/1048—Monitoring, verifying, controlling systems and methods
- A61N5/1071—Monitoring, verifying, controlling systems and methods for verifying the dose delivered by the treatment plan
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Biomedical Technology (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
- Pathology (AREA)
- Life Sciences & Earth Sciences (AREA)
- Radiology & Medical Imaging (AREA)
- Surgery (AREA)
- Urology & Nephrology (AREA)
- Epidemiology (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Image Processing (AREA)
Abstract
The invention relates to a three-dimensional dose calculation method, a three-dimensional dose calculation device and a three-dimensional dose calculation medium based on a mixed variable scale model, wherein the method comprises the following steps: 1) pretreatment: carrying out gridding physical modeling on the patient through the image information of the patient and calculating the specific energy of each voxel grid; 2) constructing a mixed variable-scale model: constructing a mixed variable-scale model according to the geometric and physical information of the gridding physical model, wherein the mixed variable-scale model comprises a dose calculation point variable-scale model and a convolution superposition variable-scale model; 3) and (3) convolution superposition calculation: calculating the dose distribution of each dose calculation point by convolution superposition; 4) and (3) post-treatment: and carrying out interpolation calculation on the dose distribution of the variable-scale dose calculation points to obtain the total-space dose distribution in the patient. By constructing the mixed variable-scale model, the rapid calculation of the dose distribution in the body of the patient is realized on the premise of ensuring the dose calculation precision, the algorithm is stable, and the universality is strong.
Description
Technical Field
The invention relates to the field of radiation therapy dose calculation, in particular to a three-dimensional dose calculation method, a three-dimensional dose calculation device and a three-dimensional dose calculation medium based on a mixed variable scale model.
Background
Radiation therapy is an important treatment for tumors, and about 70% of tumor patients need to receive radiation therapy. A radiation therapy planning system is the radiation therapy brain that is used to help physicians and physicists make optimal radiation therapy plans for oncology patients. Dose calculation is the most core technology of radiation therapy planning systems, and its accuracy and computational efficiency are the key to determine whether the planning system can be applied clinically.
Common dose calculation methods fall into two broad categories: analytical dose calculation and monte carlo dose calculation. The monte carlo dose calculation method is a stochastic algorithm that obtains the energy deposition distribution of particles in human tissue by simulating the interaction of a large number of particles with matter. The monte carlo method is computationally accurate but computationally expensive, computation time is typically on the order of hours, and requires knowledge of the exact accelerator head structure to compute the particle source item information (e.g., particle type, energy, position, orientation, etc.), while accelerator manufacturers are kept secret from the accelerator structure for commercial interest. Due to the two factors, the Monte Carlo dose calculation method cannot be widely applied to a clinical radiotherapy planning system all the time.
The analytical dose calculation method mainly comprises pen check dose calculation and point check dose calculation. Pen-kernel dose calculation is a two-dimensional dose calculation method that divides the entire beam into a number of pencil beams of finite size and obtains the dose distribution of the entire beam by superimposing the dose distributions (pen kernels) produced by the individual pencil beams. Although the pen core dose calculation is fast, the influence of non-uniform media in a human body on dose distribution cannot be accurately considered, and the precision of dose calculation is seriously reduced. The point-kernel dose calculation belongs to a three-dimensional dose calculation method, the influence of non-uniform media on the dose calculation is effectively corrected through the dose contribution of the media around the spherical integral to dose calculation points, and the method is only inferior to a Monte Carlo dose calculation method in precision and is a commonly adopted dose calculation method in a radiotherapy planning system. The point kernel dose calculation needs convolution superposition in a three-dimensional space, the calculation complexity is much higher than that of the pen kernel dose calculation, and the problem of low calculation efficiency still exists at present.
Disclosure of Invention
Technical problem to be solved
Based on the technical problems, the invention provides a three-dimensional dose calculation method, a three-dimensional dose calculation device and a three-dimensional dose calculation medium based on a mixed variable scale model, which accelerate the dose calculation speed on the premise of ensuring the precision requirement and realize the fast and efficient calculation of the three-dimensional dose field distribution in the body of a patient.
(II) technical scheme
In a first aspect, the invention provides a three-dimensional dose calculation method based on a mixed variable-scale model, which comprises the following implementation steps:
(1) pretreatment: inputting patient image information (such as CT images or CBCT images) and carrying out gridding physical modeling on the patient through an HU value-electron density mapping table, and calculating the total energy of the specific energy of each gridding voxel;
(2) constructing a mixed variable-scale model: constructing a mixed variable-scale model according to the geometric and physical information of the gridding physical model, wherein the mixed variable-scale model comprises a dose calculation point variable-scale model and a convolution superposition variable-scale model;
(3) and (3) convolution superposition calculation: taking the variable-scale model of the dose calculation points and the variable-scale model of the convolution superposition as calculation scales, and calculating the dose distribution of each dose calculation point by convolution superposition;
(4) and (3) post-treatment: and (3) calculating the spatial transformation relation between the point variable scale model and the gridded voxel points of the patient, and carrying out interpolation calculation on the dose distribution of the dose calculation points to obtain the total spatial dose distribution in the patient.
The dose calculation point variable scale model in the step (2) is constructed according to any one or combination of total energy change information and tissue heterogeneity information of the adjacent voxel ratio release of the gridding physical model; adopting small-scale calculation points in a region with larger change than the total energy of energy release, and adopting large-scale calculation points in a region with smaller change than the total energy of energy release; or adopting small-scale calculation points in the region with larger tissue heterogeneity variation and adopting large-scale calculation points in the region with smaller tissue heterogeneity variation.
The convolution superposition variable-scale model in the step (2) is constructed according to the distance between a convolution superposition voxel and a dose calculation point; the model scale is positively correlated with the distance between the convolution superposition voxel point and the dose calculation point, namely the scale is larger when the distance is farther, and the scale is smaller when the distance is smaller.
In a second aspect, the present invention provides a three-dimensional dose calculation apparatus based on a mixed scale-varying model, comprising:
(1) the preprocessing module is used for inputting dose calculation information, carrying out physical modeling on a patient and calculating the total specific energy of each voxel grid, wherein the dose calculation information comprises patient image information, an HU-electron density mapping table, plan information and treatment machine data;
(2) the mixed variable scale model construction module is used for constructing a dose calculation point variable scale model and a convolution superposition variable scale model according to the physical model information of the patient;
(3) the convolution superposition module is used for calculating the dose distribution information of each dose calculation point by a convolution superposition method based on the mixed variable-scale model;
(4) and the post-processing module is used for calculating the three-dimensional dose distribution in the patient body from the variable-scale model calculation point dose distribution through spatial transformation interpolation.
In a third aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed on a computer or processor, implements the above-described three-dimensional dose calculation method based on a mixed variable-scale model.
(III) advantageous effects
The invention provides a three-dimensional dose calculation method, a three-dimensional dose calculation device and a three-dimensional dose calculation medium based on a mixed variable scale model.
Drawings
FIG. 1 schematically illustrates a three-dimensional dose calculation method step diagram based on a hybrid variable-scale model according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a variable-scale model construction method for dose calculation points in a high-specific-energy-release total-energy gradient region at a penumbra according to an embodiment of the disclosure;
FIG. 3 schematically illustrates a convolution superposition scale-variable model construction method according to an embodiment of the present disclosure;
FIG. 4 schematically illustrates a block diagram of a computing device module according to an embodiment of the disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
In a first aspect, the present invention provides a three-dimensional dose calculation method based on a mixed variable scale model, which is implemented by referring to fig. 1, and includes:
(1) pretreatment: patient image information (such as CT images or CBCT images) and planning information and machine data information are input. The patient image is subjected to gridding treatment (uniform grids or non-uniform grids can be adopted), and the grid size in the X, Y, Z direction is 3mm in the example; the HU values of the gridded patient image are converted into electron density values through an HU value-electron density mapping table, and a gridded patient physical model is constructed. Calculating the radiation field energy fluence distribution according to the beam modeling data in the planning information and the machine data information, and then calculating the specific energy release Total Energy (TERMA) of each gridding voxel according to a formula (1);
(2) constructing a mixed variable-scale model: and (3) constructing a mixed variable-scale model according to the geometric and physical information of the gridding physical model obtained by the calculation in the step (1), wherein the mixed variable-scale model comprises a dose calculation point variable-scale model and a convolution superposition variable-scale model. The dose calculation point variable scale model is constructed according to any one or combination of adjacent voxel ratio interpretation total energy change information and tissue heterogeneity information; adopting small-scale calculation points in a region with larger change than the total energy of energy release, and adopting large-scale calculation points in a region with smaller change than the total energy of energy release; or adopting small-scale calculation points in the region with larger tissue heterogeneity variation and adopting large-scale calculation points in the region with smaller tissue heterogeneity variation. As shown in fig. 2, the processing of the point-to-scale model for dose calculation in high specific energy gradient regions at the beam penumbra is briefly described. In the example, the original 3mm grid size is adopted in the high specific energy release total energy gradient area, and the 9mm large grid size is adopted in the high specific energy release total energy uniform area; the dose calculation point variable-scale model is mainly used during sampling of dose calculation points, and the maximum number of calculation points in the example can be reduced to one ninth of the original number by processing the dose calculation point variable-scale model.
The convolution superposition process is to calculate the dose value of the dose calculation point by convolution superposition of the product of the total release energy of surrounding voxel points and the dot kernel data in the three-dimensional space, and the calculation amount is huge and time is consumed. According to the point-kernel data distribution characteristics, the variation is severe when approaching the calculation point and can be assumed to be a gentle linear distribution when departing from the calculation point. Based on the above, the embodiment accelerates the convolution and superposition speed by constructing the convolution and superposition variable-scale model on the premise of ensuring that the convolution and superposition value is basically unchanged. As shown in fig. 3, the convolution and superposition model is constructed in such a way that the distances between the convolution and superposition voxel points and the dose calculation points are positively correlated, that is, the farther the distance is, the larger the scale is, and the smaller the distance is. In this embodiment, the convolution overlay scale model uses 1mm as the minimum scale, and gradually increases in step length of 2mm, such as 1mm, 3mm, 5mm, 7mm, 9mm, 11mm …, until reaching the model boundary or threshold boundary.
(3) And (3) convolution superposition calculation: the convolution superposition calculation of the formula (2) takes a variable scale model of the dose calculation points and a variable scale model of the convolution superposition as calculation scales, and the convolution superposition calculates the dose distribution of each dose calculation point. In the specific example, a barrel string convolution superposition strategy is adopted, the three-dimensional space is divided into a plurality of direction barrel strings for convolution superposition, wherein the zenith angle uses 12 directions, the azimuth angle uses 16 directions, and 192 barrel strings are counted. When the calculation point sampling is carried out, a dose calculation point variable-scale model is used, and when the barrel string convolution superposition is carried out, a convolution superposition variable-scale model is used; compared with the traditional barrel string convolution superposition algorithm, the method is more efficient in calculation.
(4) And (3) post-treatment: and (3) calculating the spatial transformation relation between the point variable scale model and the gridded voxel points of the patient, and carrying out interpolation calculation on the dose distribution of the dose calculation points to obtain the total spatial dose distribution in the patient.
3 clinical cases of the head, the chest and the abdomen are selected, and on the premise that the calculation accuracy meets the clinical requirements, the dose calculation efficiency of the barrel string convolution superposition algorithm based on the mixed variable scale model can be improved by more than 20 times compared with the acceleration ratio of the traditional barrel string convolution superposition algorithm by comparing the dose calculation accuracy with the efficiency.
In a second aspect, the present invention provides a three-dimensional dose calculation device based on a mixed variable scale model (as shown in fig. 4), comprising:
(1) the preprocessing module is used for inputting dose calculation information, carrying out physical modeling on a patient and calculating the total specific energy of each voxel grid, wherein the dose calculation information comprises patient image information, an HU-electron density mapping table, plan information and treatment machine data;
(2) the mixed variable scale model construction module is used for constructing a dose calculation point variable scale model and a convolution superposition variable scale model according to the physical model information of the patient;
(3) the convolution superposition module is used for calculating the dose distribution information of each dose calculation point by a convolution superposition method based on the mixed variable-scale model;
(4) and the post-processing module is used for calculating the three-dimensional dose distribution in the patient body from the variable-scale model calculation point dose distribution through spatial transformation interpolation.
In a third aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed on a computer or processor, implements the above-described three-dimensional dose calculation method based on a mixed variable-scale model.
Specifically, the computer-readable medium may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer readable medium carries one or more programs which, when executed, implement the method according to an embodiment of the present application.
According to embodiments of the present application, a computer readable medium may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, optical fiber cable, radio frequency signals, etc., or any suitable combination of the foregoing.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Parts of the invention not described in detail are well known in the art.
Claims (3)
1. The three-dimensional dose calculation method based on the mixed variable-scale model is characterized by comprising the following implementation steps of:
(1) pretreatment: inputting patient image information, carrying out gridding physical modeling on a patient through an HU value-electron density mapping table, and calculating the total energy of specific energy of each gridding voxel;
(2) constructing a mixed variable-scale model: constructing a mixed variable-scale model according to the geometric and physical information of the gridding physical model, wherein the mixed variable-scale model comprises a dose calculation point variable-scale model and a convolution superposition variable-scale model;
the dose calculation point variable scale model in the step (2) is constructed according to any one or combination of total energy change information and tissue heterogeneity information of the adjacent voxel ratio release of the gridding physical model; adopting small-scale calculation points in a region where the ratio of adjacent voxels to the total energy of the adjacent; adopting small-scale calculation points in the region with larger tissue heterogeneity variation of adjacent voxels, and adopting large-scale calculation points in the region with smaller tissue heterogeneity variation;
the convolution superposition variable-scale model in the step (2) is constructed according to the distance between a convolution superposition voxel and a dose calculation point; the distance between the model scale and the convolution superposition voxel point and the dose calculation point is in positive correlation, namely the scale is larger when the distance is longer, and the scale is smaller when the distance is smaller;
(3) and (3) convolution superposition calculation: taking the variable-scale model of the dose calculation points and the variable-scale model of the convolution superposition as calculation scales, and calculating the dose distribution of each dose calculation point by convolution superposition;
(4) and (3) post-treatment: and (3) carrying out interpolation calculation on the dose distribution of the dose calculation points to obtain the total-space dose distribution in the patient body through the spatial transformation relation between the dose calculation point variable-scale model and the gridded voxel points of the patient.
2. Three-dimensional dose calculation device based on mix becomes scale model, its characterized in that includes:
(1) the preprocessing module is used for inputting dose calculation information, carrying out physical modeling on a patient and calculating the total specific energy of each voxel grid, wherein the dose calculation information comprises patient image information, an HU-electron density mapping table, plan information and treatment machine data;
(2) the mixed variable scale model construction module is used for constructing a dose calculation point variable scale model and a convolution superposition variable scale model according to the physical model information of the patient;
the dose calculation point variable scale model is constructed according to any one or combination of adjacent voxel ratio interpretation total energy change information and tissue heterogeneity information; adopting small-scale calculation points in a region with larger change than the total energy of energy release, and adopting large-scale calculation points in a region with smaller change than the total energy of energy release; or adopting small-scale calculation points in the region with larger tissue heterogeneity variation and adopting large-scale calculation points in the region with smaller tissue heterogeneity variation; the construction principle of the convolution superposition model is that the distance between a convolution superposition voxel point and a dose calculation point is in positive correlation, namely the scale is larger when the distance is longer, and the scale is smaller when the distance is smaller;
(3) the convolution superposition module is used for calculating the dose distribution information of each dose calculation point by a convolution superposition method based on the mixed variable-scale model;
(4) and the post-processing module is used for calculating point dose distribution in the dose calculation point variable-scale model and obtaining three-dimensional dose distribution in the patient body through spatial transformation interpolation calculation.
3. A computer-readable storage medium having stored thereon a computer program, characterized in that: when run on a computer or processor, implements the hybrid variable-scale model-based three-dimensional dose calculation method of claim 1.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010407021.0A CN111494815B (en) | 2020-05-14 | 2020-05-14 | Three-dimensional dose calculation method, device and medium based on mixed variable-scale model |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010407021.0A CN111494815B (en) | 2020-05-14 | 2020-05-14 | Three-dimensional dose calculation method, device and medium based on mixed variable-scale model |
Publications (2)
Publication Number | Publication Date |
---|---|
CN111494815A CN111494815A (en) | 2020-08-07 |
CN111494815B true CN111494815B (en) | 2022-04-29 |
Family
ID=71865262
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010407021.0A Active CN111494815B (en) | 2020-05-14 | 2020-05-14 | Three-dimensional dose calculation method, device and medium based on mixed variable-scale model |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111494815B (en) |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112017166B (en) * | 2020-08-17 | 2024-06-14 | 苏州求索健康科技有限公司 | Method for calculating radiation dose distribution of radiotherapy pencil beam based on CPU/GPU hybrid cluster |
CN112086172A (en) * | 2020-09-14 | 2020-12-15 | 广州瑞多思医疗科技有限公司 | Three-dimensional dose calculation method, computer equipment and readable medium |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102201036A (en) * | 2011-05-16 | 2011-09-28 | 四川大学 | Realization of convolution superposition algorithm in graphics processing unit (GPU) acceleration dosage calculation |
CN102812465A (en) * | 2010-03-08 | 2012-12-05 | 皇家飞利浦电子股份有限公司 | Scheduling of dose calculation tasks including efficient dose calculation |
CN104066479A (en) * | 2011-09-29 | 2014-09-24 | 约翰霍普金斯大学 | Dose computation for radiation therapy using heterogeneity compensated superposition |
CN110013613A (en) * | 2019-04-16 | 2019-07-16 | 东莞东阳光高能医疗设备有限公司 | A kind of boron neutron capture therapy planning system |
CN110570923A (en) * | 2018-06-06 | 2019-12-13 | 北京连心医疗科技有限公司 | mixed Monte Carlo radiotherapy reverse optimization method, equipment and storage medium |
CN110652661A (en) * | 2019-09-30 | 2020-01-07 | 中北大学 | Convolution superposition dosage calculation system |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101477203B (en) * | 2009-01-22 | 2012-03-14 | 中国科学技术大学 | Resolution Monte Carto dosage computing method |
US20120041685A1 (en) * | 2010-07-13 | 2012-02-16 | Vanderbilt University | System and method for estimating radiation dose and distribution using medium-dependent-correction based algorithms (mdc) |
US9251302B2 (en) * | 2014-01-14 | 2016-02-02 | Mitsubishi Electric Research Laboratories, Inc. | System and method for planning a radiation therapy treatment |
CN106199672B (en) * | 2016-06-30 | 2019-01-08 | 中国科学院合肥物质科学研究院 | A kind of convolution superposition dose calculation methodology based on Monte Carlo photonic analogy |
-
2020
- 2020-05-14 CN CN202010407021.0A patent/CN111494815B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102812465A (en) * | 2010-03-08 | 2012-12-05 | 皇家飞利浦电子股份有限公司 | Scheduling of dose calculation tasks including efficient dose calculation |
CN102201036A (en) * | 2011-05-16 | 2011-09-28 | 四川大学 | Realization of convolution superposition algorithm in graphics processing unit (GPU) acceleration dosage calculation |
CN104066479A (en) * | 2011-09-29 | 2014-09-24 | 约翰霍普金斯大学 | Dose computation for radiation therapy using heterogeneity compensated superposition |
CN110570923A (en) * | 2018-06-06 | 2019-12-13 | 北京连心医疗科技有限公司 | mixed Monte Carlo radiotherapy reverse optimization method, equipment and storage medium |
CN110013613A (en) * | 2019-04-16 | 2019-07-16 | 东莞东阳光高能医疗设备有限公司 | A kind of boron neutron capture therapy planning system |
CN110652661A (en) * | 2019-09-30 | 2020-01-07 | 中北大学 | Convolution superposition dosage calculation system |
Also Published As
Publication number | Publication date |
---|---|
CN111494815A (en) | 2020-08-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
JP3730514B2 (en) | System and method for radiation dose calculation | |
JP6437812B2 (en) | Method and radiation therapy system for optimizing radiation dose for radiation therapy treatment | |
EP3695882A1 (en) | Computing radiotherapy dose distribution | |
CN102036712B (en) | System for radiation therapy and method for determining radiation therapy parameters | |
US20060259282A1 (en) | Deterministic computation of radiation transport for radiotherapy dose calculations and scatter correction for image reconstruction | |
EP3357537A1 (en) | Geometric model establishment method based on medical image data | |
JP2006142043A (en) | Automated optimization method for radiotherapy dose | |
Nguyen et al. | A comparison of Monte Carlo dropout and bootstrap aggregation on the performance and uncertainty estimation in radiation therapy dose prediction with deep learning neural networks | |
Wu et al. | Improving proton dose calculation accuracy by using deep learning | |
CN111494815B (en) | Three-dimensional dose calculation method, device and medium based on mixed variable-scale model | |
CN102184330A (en) | Image feature and smart regressive model-based method for optimizing intensity modulated radiotherapy plan | |
US20190325637A1 (en) | Method for establishing smooth geometric model based on data of medical image | |
Pastor-Serrano et al. | Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy | |
CN109125952B (en) | Convolution superposition energy deposition calculation method based on kernel model | |
US9251302B2 (en) | System and method for planning a radiation therapy treatment | |
Neph et al. | Parallel beamlet dose calculation via beamlet contexts in a distributed multi‐GPU framework | |
CN113599728B (en) | Radiotherapy dose prediction method and device | |
CN103987426A (en) | Method for preparing irradiation plan for moving target volume without movement compensation | |
Zhang et al. | Convolution neural network toward Monte Carlo photon dose calculation in radiation therapy | |
CN110246562A (en) | Determine the method, apparatus and computer system of the sub-beam intensity in radiotherapy system | |
Zhou et al. | Feasibility study of deep learning‐based markerless real‐time lung tumor tracking with orthogonal X‐ray projection images | |
CN110310743B (en) | Monte Carlo dose calculation method, equipment and storage medium | |
Vazquez et al. | A deep learning-based approach for statistical robustness evaluation in proton therapy treatment planning: a feasibility study | |
Roland et al. | A method for deriving a 4D‐interpolated balanced planning target for mobile tumor radiotherapy | |
CN112419439B (en) | Method for rapidly inverting proton heavy ion energy in treatment plan |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant | ||
PE01 | Entry into force of the registration of the contract for pledge of patent right |
Denomination of invention: Three-dimensional dose calculation method, device, and medium based on hybrid variable scale model Effective date of registration: 20230307 Granted publication date: 20220429 Pledgee: Industrial Bank Limited by Share Ltd. Chaohu branch Pledgor: ANHUI WISDOM TECH CO.,LTD. Registration number: Y2023980034118 |
|
PE01 | Entry into force of the registration of the contract for pledge of patent right |