Automatic Planning for Nasopharyngeal Carcinoma Based on Progressive Optimization in RayStation Treatment Planning System.

Yiwei YangKainan ShaoJie ZhangMing ChenYuanyuan ChenGuoping Shan

Published in: Technology in cancer research & treatment (2020)

IronPython language designed by RayStation TPS has clinical application value in the design of automatic radiotherapy plan for nasopharyngeal carcinoma. The dose distribution of tumor target and organs at risk in the APs was similar or better than those in the MPs. The time of manual operation in the plan design showed a sharp reduction, thus significantly improving the work efficiency in clinical application.

Keyphrases

deep learning
machine learning
early stage
multiple sclerosis
autism spectrum disorder
radiation therapy
locally advanced
radiation induced
neural network