A comprehensive multifaceted technical evaluation framework for implementation of auto-segmentation models in radiotherapy

Abstract Background Manual contouring of organs at risk in radiotherapy is time-consuming, taking 1-4 hours per case. Automatic segmentation using deep learning has emerged as a promising solution, with many commercial options now available. However, these methods require rigorous validation before...

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Үндсэн зохиолчид:	Robert Poel, Elias Rüfenacht, Stefan Scheib, Hossein Hemmatazad, Reinhardt Krcek, Sébastien Tran, Edourd Romano, Susanne Rogers, Sonja Stieb, Mohamed Riyas Poolakundan, Hissa Hussein Al-Abdulla, Robert Foerster, Christina Schröder, Christoph Oehler, Julian Hong, Sebastiaan Breedveld, Nicolaus Andratschke, Peter Manser, Michael K. Fix, Daniel M. Aebersold, Mauricio Reyes, Ekin Ermiş
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	Nature Portfolio 2025-07-01
Цуврал:	Communications Medicine
Онлайн хандалт:	https://doi.org/10.1038/s43856-025-01048-6
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!