Automatic Planning of Whole Breast Radiation Therapy Using Machine Learning Models

Automatic Planning of Whole Breast Radiation Therapy Using Machine Learning Models

Purpose: To develop an automatic treatment planning system for whole breast radiation therapy (WBRT) based on two intensity-modulated tangential fields, enabling near-real-time planning.Methods and Materials: A total of 40 WBRT plans from a single institution were included in this study under IRB ap...

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Bibliographic Details
Main Authors: Yang Sheng, Taoran Li, Sua Yoo, Fang-Fang Yin, Rachel Blitzblau, Janet K. Horton, Yaorong Ge, Q. Jackie Wu
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-08-01
Series:Frontiers in Oncology
Subjects:
whole breast radiation therapy
breast cancer
machine learning
auto planning
random forest
electronic compensation
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2019.00750/full

Internet

https://www.frontiersin.org/article/10.3389/fonc.2019.00750/full

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