Deep learning based automatic segmentation of organs-at-risk for 0.35 T MRgRT of lung tumors

Abstract Background and purpose Magnetic resonance imaging guided radiotherapy (MRgRT) offers treatment plan adaptation to the anatomy of the day. In the current MRgRT workflow, this requires the time consuming and repetitive task of manual delineation of organs-at-risk (OARs), which is also prone t...

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Autori principali:	Marvin F. Ribeiro, Sebastian Marschner, Maria Kawula, Moritz Rabe, Stefanie Corradini, Claus Belka, Marco Riboldi, Guillaume Landry, Christopher Kurz
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	BMC 2023-08-01
Serie:	Radiation Oncology
Soggetti:	Deep learning Auto-segmentation MR-Linac MRI-guidance Thorax
Accesso online:	https://doi.org/10.1186/s13014-023-02330-4
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