NeuralDAO: Incorporating neural network generated dose into direct aperture optimization for end‐to‐end IMRT planning-Reference-Cited by-同舟云学术

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NeuralDAO: Incorporating neural network generated dose into direct aperture optimization for end‐to‐end IMRT planning

Published:2021-08-25 Issue:10 Volume:48 Page:5624-5638
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Liu Cong¹²³,Ni Xinye²³,Jin Xiance⁴⁵,Si Wen¹⁶

Affiliation:

1. Faculty of Business Information Shanghai Business School Shanghai China

2. Radiation Oncology Center Affiliated Changzhou No. 2 People's Hospital of Nanjing Medical University Changzhou China

3. Department is Center of Medical Physics Center of Medical Physics Nanjing Medical University Changzhou China

4. Radiotherapy Center Department The First Affiliated Hospital of Wenzhou Medical University Wenzhou China

5. Basic Medical School Wenzhou Medical University Wenzhou China

6. Department of Rehabilitation Huashan Hospital, Fudan University Shanghai China

Funder

Natural Science Foundation of Shanghai

China Postdoctoral Science Foundation

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.15155

Reference33 articles.

1. Estimating the demand for radiotherapy from the evidence: A review of changes from 2003 to 2012

2. Direct aperture optimization: A turnkey solution for step-and-shoot IMRT

3. A Column Generation Approach to Radiation Therapy Treatment Planning Using Aperture Modulation

4. Aperture shape optimization for IMRT treatment planning

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning applied to dose prediction in external radiation therapy: A narrative review;Cancer/Radiothérapie;2024-08

2. An ultra-fast deep-learning-based dose engine for prostate VMAT via knowledge distillation framework with limited patient data;Physics in Medicine & Biology;2022-12-19

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