Auto-segmentation of organs-of-interest clinical acceptability & reproducibility framework in head and neck cancer

Background and purpose: Auto-segmentation of organs-of-interest (OOI) in cancer patients is essential for facilitating radiotherapy planning and reducing inter-observer variability. Deep learning-based auto-segmentation models have shown promise, but limited transparency and reproducibility hinder t...

Ausführliche Beschreibung

Bibliografische Detailangaben

Hauptverfasser:	Joseph Marsilla, Mattea L. Welch, Joshua Siraj, Clare McElcheran, Jun Won Kim, Denis Tkachuck, Sejin Kim, John Cho, Ezra Hahn, Ali Hosni, J.C. Jacinto, Michal Kazmierski, Katrina Rey-McIntyre, Shao Hui Huang, Tirth Patel, Tony Tadic, Scott Bratman, Andrew Hope, Benjamin Haibe-Kains
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Elsevier 2026-05-01
Schriftenreihe:	Physics and Imaging in Radiation Oncology
Schlagworte:	Auto-segmentation Head and neck cancer Organs-of-interest Framework Clinical assessment Generalizability assessment
Online-Zugang:	http://www.sciencedirect.com/science/article/pii/S2405631626001156
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