生物医学工程研究2018，Vol.37Issue(2)：132-137,6.DOI:10.19529/j.cnki.1672-6278.2018.02.03
基于支持向量回归的呼吸运动预测技术的研究
Study on predicting respiratory motion with support vector regression
摘要
Abstract
The target is usually tracked in real time at thoracic and abdominal radiotherapy due to the effect of respiratory motion,the prediction is necessary to compensate the system latency.A prediction method based on support vector regression (SVR) was pro-posed, a part of historical data for training was selected,and then the output was calculated according to the training model when there was a new sequence.Furthermore, the training set would be dynamically updated and the accurate online support vector regression model was achieved.The experiment selected seven respiratory motion data ;the model was trained by on-line and off-line method, then prediction was carried out.The mean absolute error was 0.42 mm, 0.30 mm, respectively.The respiratory motion is accurately described by the online accurate support vector regression,and the results with high precision can satisfy practical application.关键词
放射治疗/呼吸运动/预测算法/支持向量回归/核函数Key words
Radiotherapy/Respiratory motion/Support vector regression/Prediction algorithm/Kernel function分类
医药卫生引用本文复制引用
康开莲,童蕾,万伟权,孙海涛,陈超敏..基于支持向量回归的呼吸运动预测技术的研究[J].生物医学工程研究,2018,37(2):132-137,6.基金项目
广东省科技计划项目(2015A020214013). （2015A020214013）
