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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Hlavní autoři:	Aly Khalifa, Jeff D. Winter, Tony Tadic, Thomas G. Purdie, Chris McIntosh
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Elsevier 2024-10-01
Edice:	Physics and Imaging in Radiation Oncology
Témata:	Automation Treatment planning Adaptive radiotherapy Prostate cancer Machine learning Artificial intelligence
On-line přístup:	http://www.sciencedirect.com/science/article/pii/S2405631624001192
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