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Dose prediction method and device for robot radiotherapy equipment

A technology for radiation therapy and dose prediction, applied in radiation therapy, therapy, X-ray/γ-ray/particle irradiation therapy, etc.

Inactive Publication Date: 2021-12-10
BEIHANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, model-based algorithms still rely on approximations and only partially deal with physical processes in the microscopic domain involving microscopic absorption of energy delivered by radiation fields
Monte Carlo simulation calculates the dose distribution based on the computer simulation of the physical process of particles in the substance. It has high precision in the field of dose calculation and is often used to verify the accuracy of other dose calculation algorithms, but Monte Carlo dose calculation takes a long time. , it is difficult to meet the timeliness requirements in practical applications
In short, the current dose calculation method is difficult to achieve high precision and high efficiency at the same time

Method used

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  • Dose prediction method and device for robot radiotherapy equipment

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no. 1 example 1

[0022] figure 1 It is a schematic flow chart of a dose prediction method for a robot radiation therapy device according to the first embodiment of the present invention, as shown in figure 1 As shown, the method includes the following two steps.

[0023] Step S101: training the radiotherapy dose prediction model. Specifically, the patient phantom is established according to the patient's medical image, and the phantom is constructed according to the mapping relationship between the pixel value of the medical image and the physical material and electron density; according to the parameters of the treatment head of the robot radiotherapy equipment, the first calculation method of radiotherapy dose is used Calculate the dose distribution H of the single shot field of the patient phantom; calculate the dose distribution L of the single shot field of the patient phantom by using the second calculation method of radiotherapy dose according to the parameters of the treatment head of...

no. 1 example

[0028] In an optional embodiment, the deep learning neural network is HD U-Net. figure 2 It is a schematic diagram of the deep learning neural network structure of a robot radiotherapy equipment dose prediction method according to the first embodiment of the present invention, as shown in figure 2As shown, HD U-Net contains five hierarchical structures to reduce the feature size. Through the 2×2×2 pooling layer (Pooling) between each layer, the feature map (Feature Map) is finally reduced to 6× at the bottom layer. 4×6 to learn local and global features. In each layer, a convolutional kernel of size 3×3×3 is used and zero padding is used to maintain the size of the feature. In the first half of HD U-Net, each convolution step generates 4 feature maps (filters). In the remaining half, except for the last convolution step, the number of feature maps per convolution layer increases by 4 from bottom to top. The last convolution step produces one channel as the final output. ...

Embodiment 2

[0034] The embodiment of the present invention provides a device for predicting the dose of robotic radiotherapy equipment, which is mainly used to implement the method for predicting the dose of robotic radiotherapy equipment provided in the above-mentioned content of the embodiment of the present invention. The following describes the robotic radiotherapy equipment provided by the embodiment of the present invention The dose prediction device will be introduced in detail.

[0035] image 3 It is a schematic structural diagram of a device for predicting doses of robotic radiotherapy equipment according to the second embodiment of the present invention. Such as image 3 As shown, the robot radiotherapy equipment dose prediction device 200 includes the following modules:

[0036] Model training module 201, which is used to establish a patient phantom according to the medical image of the patient, and the phantom is constructed according to the mapping relationship between the...

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Abstract

The invention discloses a dose prediction method and device for robot radiotherapy equipment. The method comprises the steps: performing model training, and building a patient model body according to a medical image of a patient; according to parameters of a treatment head of robot radiotherapy equipment, calculating dose distribution H of a single radiation field of a patient die body by using a first radiotherapy dose calculation method; according to the parameters of the treatment head of the robot radiotherapy equipment, calculating dose distribution L of the single radiation field of the patient die body by using a second radiotherapy dose calculation method; taking the L and the medical image of the patient as inputs, taking the H as an output, and sending the inputs into a deep learning neural network for training to obtain a radiotherapy dose prediction network; predicting doses, and calculating the dose distribution L * of the single radiation field of any patient die body by using a second radiotherapy dose calculation method; and obtaining the dose distribution H * of the single radiation field of any patient die body, predicted by the output end of the radiotherapy dose prediction network. The technical effect that one algorithm is used for predicting the calculation result output by the other algorithm is achieved through the deep learning network.

Description

technical field [0001] The invention relates to the technical field of radiotherapy dose calculation, in particular to a dose prediction method of a robot radiotherapy equipment. Background technique [0002] Malignant tumors seriously endanger human health. Seventy percent of tumor patients need radiation therapy. Before radiation therapy, doctors will formulate a radiation therapy plan. Dose calculation is an important link in the process of radiotherapy planning, and the effectiveness of dose calculation determines the quality of radiotherapy planning. In the prior art, dose calculation methods are divided into three categories: factor-based algorithms, model-based algorithms, and Monte Carlo simulation. The factor-based algorithm uses a semi-empirical approach to address tissue heterogeneity and surface curvature based on efficient spatial dosimetry, has the advantage of being computationally fast, and does not require the distinction between the subsequent energy trans...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61N5/10
CPCA61N5/1001A61N5/103A61N5/1048A61N5/1071A61N5/1069A61N2005/1061A61N2005/1054
Inventor 刘博李晗周付根
Owner BEIHANG UNIV
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