A neural network prediction device for vmat radiotherapy planning

A technology of neural network and prediction device, applied in the direction of biological neural network model, neural architecture, neural learning method, etc., can solve the problems of large error, poor performance, single control object, etc., achieve small performance error, good effect, and improve efficiency Effect

Active Publication Date: 2022-01-28
SICHUAN UNIV
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AI Technical Summary

Problems solved by technology

[0008] Based on the above problems, the present invention provides a neural network prediction device for VMAT radiotherapy plan, which is used to solve the problems of single control object, poor performance and large error in the quality control method of radiotherapy plan in the prior art

Method used

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  • A neural network prediction device for vmat radiotherapy planning
  • A neural network prediction device for vmat radiotherapy planning
  • A neural network prediction device for vmat radiotherapy planning

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Embodiment

[0067] Such as Figure 1-Figure 2 As shown, a neural network prediction device for VMAT radiotherapy planning includes the following steps:

[0068] Step 1: Data preparation, obtain the data and labels of multiple cases of VMAT radiotherapy planning quality control, the data format is dicom, the file label is its corresponding gamma pass rate, and preprocess the dicom files, and then divide the data into training sets and the test set, the gamma pass rate label is the gold standard based on the motif measurement;

[0069] Data preparation in step 1 includes the following steps:

[0070] Step 1.1: Acquire data and labels, obtain data and labels of multiple cases of VMAT radiotherapy plan quality control, use matlab to calculate radiotherapy plan characteristics and accelerator related parameters from dicom original files, and calculate multiple dicom original files for each case Accelerator parameters and multiple parameters related to radiotherapy planning, wherein, there ar...

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Abstract

The invention relates to the technical field of quality control of radiotherapy plans, in particular to a neural network prediction device for VMAT radiotherapy plans, which is used to solve the problem of single control object, poor performance and large errors in the quality control methods of radiotherapy plans in the prior art question. The invention includes a data preparation module and a model design module, which are used to establish a multi-branch neural network model. The input of the multi-branch neural network model is processed to obtain multi-dimensional features, and then the predicted gamma pass rate is output; the model training module is used to perform first Feature extraction, and regression calculation of the gamma pass rate, and then backpropagation, update the parameters of the model, and iterate multiple times until good model parameters are obtained; the model test module is used to output the predicted gamma pass rate after forward calculation; In the present invention, radiotherapy plans for more body parts can be accepted through the above steps, with smaller performance errors and better effects.

Description

technical field [0001] The invention relates to the technical field of quality control of radiotherapy plans, and more particularly relates to a neural network prediction device for VMAT radiotherapy plans. Background technique [0002] In clinical tumor treatment, surgery, radiotherapy, and chemotherapy are the three most important treatment methods. Due to the wide indications and high selectivity of radiotherapy, more than 70% of malignant tumor patients need to be treated at a certain stage. Radiation therapy, modern radiotherapy techniques mainly include intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT). Radiation therapy is an important cancer treatment method, which uses high-energy rays to irradiate target cells , destroy its DNA to stop growth, and make it lose the ability to divide and replicate. Since the accelerator used in its treatment is very precise and sensitive to the environment and the complexity of the treatment pla...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06N3/04G06N3/06G06N3/08G06K9/62G16H50/20G16H50/70
CPCG06N3/061G06N3/084G16H50/20G16H50/70G06N3/045G06F18/253G06F18/214
Inventor 张蕾李光俊章毅谢立章刘文杰胡婷柏森
Owner SICHUAN UNIV
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