Improving efficiency of training a virtual treatment planner network via knowledge‐guided deep reinforcement learning for intelligent automatic treatment planning of radiotherapy-Reference-Cited by-同舟云学术

Improving efficiency of training a virtual treatment planner network via knowledge‐guided deep reinforcement learning for intelligent automatic treatment planning of radiotherapy

Published:2021-02-16 Issue:4 Volume:48 Page:1909-1920
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Shen Chenyang¹²,Chen Liyuan¹,Gonzalez Yesenia¹²,Jia Xun¹²

Affiliation:

1. Medical Artificial Intelligence and Automation (MAIA) Laboratory Department of Radiation Oncology University of Texas Southwestern Medical Center Dallas TX USA

2. Innovative Technology Of Radiotherapy Computation and Hardware (iTORCH) Laboratory Department of Radiation Oncology University of Texas Southwestern Medical Center Dallas TX USA

Funder

National Institutes of Health

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14712

Reference39 articles.

1. Intensity-Modulated Radiation Therapy Dose Prescription, Recording, and Delivery: Patterns of Variability Among Institutions and Treatment Planning Systems

2. Variation in external beam treatment plan quality: An inter-institutional study of planners and planning systems

3. Optimization of importance factors in inverse planning