Prior knowledge based deep learning auto-segmentation in magnetic resonance imaging-guided radiotherapy of prostate cancer

Background and purpose: Automation is desirable for organ segmentation in radiotherapy. This study compared deep learning methods for auto-segmentation of organs-at-risk (OARs) and clinical target volume (CTV) in prostate cancer patients undergoing fractionated magnetic resonance (MR)-guided adaptiv...

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Dettagli Bibliografici

Autori principali:	Maria Kawula, Marica Vagni, Davide Cusumano, Luca Boldrini, Lorenzo Placidi, Stefanie Corradini, Claus Belka, Guillaume Landry, Christopher Kurz
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2023-10-01
Serie:	Physics and Imaging in Radiation Oncology
Soggetti:	Auto-segmentation Patient-specific models Spatial transformer layer Deep learning MRgRT MR-Linac
Accesso online:	http://www.sciencedirect.com/science/article/pii/S2405631623000891
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