Incorporating patient-specific information for the development of rectal tumor auto-segmentation models for online adaptive magnetic resonance Image-guided radiotherapy

Background and purpose: In online adaptive magnetic resonance image (MRI)-guided radiotherapy (MRIgRT), manual contouring of rectal tumors on daily images is labor-intensive and time-consuming. Automation of this task is complex due to substantial variation in tumor shape and location between patien...

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Autors principals:	Chavelli M. Kensen, Rita Simões, Anja Betgen, Lisa Wiersema, Doenja M.J. Lambregts, Femke P. Peters, Corrie A.M. Marijnen, Uulke A. van der Heide, Tomas M. Janssen
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2024-10-01
Col·lecció:	Physics and Imaging in Radiation Oncology
Matèries:	Rectal cancer Deep learning Auto-segmentation GTV MRI-guided radiotherapy Online adaptive radiotherapy
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S2405631624001180
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