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Dose calculation system, dose quality assurance system and storage medium

A computing system and dose technology, applied in the direction of calculation, calculation model, computer parts, etc., can solve the problems of complex modeling process, slow determination of Monte Carlo parameters, slow modeling speed of Monte Carlo dose algorithm, etc., to achieve The effect of speeding up the modeling process

Pending Publication Date: 2020-12-25
SHANGHAI UNITED IMAGING HEALTHCARE
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  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the requirement of high precision, the modeling process of the fast Monte Carlo algorithm is relatively complicated, and there are many parameters that need to be adjusted, which leads to the slow determination of the Monte Carlo parameters in the Monte Carlo algorithm, making the construction of the Monte Carlo dose algorithm difficult. Mode is slower

Method used

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  • Dose calculation system, dose quality assurance system and storage medium
  • Dose calculation system, dose quality assurance system and storage medium
  • Dose calculation system, dose quality assurance system and storage medium

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Experimental program
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Embodiment 1

[0041] figure 1 It is a schematic flowchart of steps executed by a processor in a dose calculation system provided by Embodiment 1 of the present invention. This embodiment is applicable to the case of calculating dose distribution information. Such as figure 1 As shown, the steps performed by the processor specifically include:

[0042] S110. Acquiring dose-related parameters related to radiotherapy equipment.

[0043] In this embodiment, dose-related parameters can be understood as parameters that affect dose values. Optionally, the dose-related parameters include machine parameters, field information and at least one target position information. Wherein, the radiation field information may be the target area where the radiation points to and passes through, and specifically may be information such as the size and position of the target area. In one embodiment, the fields may be configured as square fields of different sizes with the center of the field on the central a...

Embodiment 2

[0051] figure 2 It is a schematic flowchart of steps executed by a processor in a dose calculation system provided by Embodiment 2 of the present invention. This embodiment is further optimized on the basis of the above solution. Such as figure 2 As shown, the methods include:

[0052] S210. Acquire training sample data, where the training sample data includes different sample dose parameters and sample dose information corresponding to the sample dose parameters.

[0053] In this embodiment, the training sample data can be generated based on the water tank doses of different field sizes under different machine parameters. Optionally, a Monte Carlo algorithm may be used to determine sample dose information under multiple sample dose parameters, and to determine training sample data based on the sample dose information under multiple sample dose parameters. In this embodiment, the Monte Carlo algorithm can be used to calculate the dose distribution in the water tank to re...

Embodiment 3

[0064] Figure 3a It is a flowchart of a dose prediction method provided by Embodiment 3 of the present invention. This embodiment provides a preferred embodiment on the basis of the above solutions. Such as Figure 3a As shown, the method includes

[0065] S310. Use a Monte Carlo algorithm to calculate sample dose information under different sample dose parameters, and use a dose point associated with the sample dose information as a sample dose point.

[0066] Optionally, the sample dose parameters include machine parameters, field information and at least one target position information. For specific machine parameters, shot field information and target position information, please refer to the above-mentioned embodiments, which will not be repeated here.

[0067] S320. Select 85% of sample dose points as training dose points, and the remaining 15% of sample dose points as test dose points.

[0068] 85% of the total number of sample dose points can be selected as train...

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Abstract

The embodiment of the invention discloses a dose calculation system, a dose quality assurance system and a storage medium. The dose calculation system comprises a processor, and the processor is configured to process the following steps: acquiring dose-related parameters related to radiotherapy equipment; inputting the dose-related parameters into a trained dose calculation model to obtain outputinformation of the dose calculation model, wherein the dose calculation model is constructed based on a deep learning model; and determining dose distribution information according to the output information. According to the embodiment of the invention, the dose calculation model is constructed and trained based on the deep learning model, automatic modeling is realized, a user does not need to manually adjust parameters, the calculation speed is high, the calculation efficiency of dose distribution prediction is improved, and the modeling process of rapid Monte Carlo dose calculation in a radiotherapy system is accelerated; and moreover, the dose calculation model can be used for guaranteeing the quality of the radiation dose, improves the calculation efficiency, and is high in accuracy.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of medical equipment, in particular to a dose calculation system, a dose quality assurance system and a storage medium. Background technique [0002] The Treatment Plan System (TPS) is a medical software product. By modeling the radiation source and the patient, a set of parameters related to radiation therapy can be determined through an optimization algorithm, so that the parameters given by the doctor can be achieved when the parameters are executed. Prescribed dosage. With the pursuit of accurate dose calculation, fast Monte Carlo (Monte Carlo) dose calculation in the treatment planning system becomes particularly important. The calculation speed of the fast Monte Carlo algorithm can reach the second level, which can meet the clinical speed requirements. However, due to the requirement of high precision, the modeling process of the fast Monte Carlo algorithm is relatively comp...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H50/50G06K9/62G06N20/00
CPCG16H50/50G06N20/00G06F18/214
Inventor 金朝傅佳棋刘艳芳
Owner SHANGHAI UNITED IMAGING HEALTHCARE
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