Machine learning automated treatment planning for online magnetic resonance guided adaptive radiotherapy of prostate cancer

Background and purpose: No best practices currently exist for achieving high quality radiation therapy (RT) treatment plan adaptation during magnetic resonance (MR) guided RT of prostate cancer. This study validates the use of machine learning (ML) automated RT treatment plan adaptation and benchmar...

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Bibliographic Details
Main Authors: Aly Khalifa, Jeff D. Winter, Tony Tadic, Thomas G. Purdie, Chris McIntosh
Format: Article
Language:English
Published: Elsevier 2024-10-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631624001192
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