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Automatic design method for nasopharyngeal carcinoma radiotherapy plan based on machine learning

A technology of radiotherapy and machine learning for nasopharyngeal carcinoma, applied in machine learning, computer-aided medical procedures, instruments, etc., to achieve fast and simple search, increase generation speed, and reduce time burden

Active Publication Date: 2018-08-03
福建省肿瘤医院
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Current methods are not yet capable of meeting such requirements

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  • Automatic design method for nasopharyngeal carcinoma radiotherapy plan based on machine learning
  • Automatic design method for nasopharyngeal carcinoma radiotherapy plan based on machine learning
  • Automatic design method for nasopharyngeal carcinoma radiotherapy plan based on machine learning

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[0048] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0049] The present invention provides a method for generating an automatic plan for nasopharyngeal carcinoma based on machine learning, which is implemented according to the following steps:

[0050] Step S1: Establish a case template database, and determine the objective function corresponding to the case for dose-volume histogram data acquisition;

[0051] Step S2: Obtain the organ overlap volume histogram (OverlapVolume Histogram, OVH) of the case in the case template database, and store it in the case template database;

[0052] In this example, if figure 2 shown, for the OVH data and the resulting image, as image 3 Shown is the histogram of organ overlapping volumes.

[0053] Step S3: Acquiring the organ overlapping volume histogram of the patient case;

[0054] Step S4: if Figure 4 As shown, based on the structural similarit...

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Abstract

The invention relates to an automatic design method for a nasopharyngeal carcinoma radiotherapy plan based on machine learning, and provides a method for searching for a patient optimal objective function based on Overlap Volume Histogram (OVH) data and in combination with machine learning nearest neighbor method. The method comprises establishing a template library by using existing data, searching for the most similar cases in the OVH data and the template library of newly enrolled patients by using the machine learning nearest neighbor method, and planning the radiotherapy plan of the newlyenrolled cases by using the objective function of the searched radiotherapy plan of the newly enrolled cases. The case template is searched without the need for human subjective factors, and the patient's nasopharyngeal carcinoma radiotherapy plan is automatically designed.

Description

technical field [0001] The invention relates to the fields of computer graphics and machine learning, in particular to a machine learning-based automatic design method for radiotherapy plans for nasopharyngeal carcinoma. Background technique [0002] Radiation therapy is one of the three main treatments for malignant tumors, and about 60% to 70% of malignant tumor patients need to receive radiation therapy. The purpose of radiotherapy is to increase the gain ratio of radiotherapy, that is, to maximize the concentration of radiation dose into the tumor, so that the surrounding normal tissues are less or protected from unnecessary irradiation. Nasopharyngeal carcinoma is a high-incidence head and neck tumor in southern China and Asian Chinese. Radiation therapy is currently the main treatment for nasopharyngeal carcinoma. The intensity modulated radiation therapy (IMRT) technique is suitable for the treatment of nasopharyngeal carcinoma because: (1) there are many important n...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16H30/20G16H50/70G06N99/00
CPCG06N20/00G16H30/20G16H50/70
Inventor 柏朋刚陈济鸿戴艺涛陈传本翁星
Owner 福建省肿瘤医院
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