Domain-Adaptive and Per-Fraction Guided Deep Learning Framework for Magnetic Resonance Imaging-Based Segmentation of Organs at Risk in Gynecologic Cancers
Purpose: The integration of magnetic resonance imaging into radiation therapy (RT) treatment necessitates automated segmentation algorithms for fast and accurate adaptive interventions, particularly in magnetic resonance imaging-integrated linear accelerator (MR-linac or MRL) treatment systems. Howe...
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| Main Authors: | Reza Kalantar, PhD, Manasi Ingle, FRCR, Romelie Rieu, BA, BmBCh, Sebastian Curcean, MD, Jessica Mary Winfield, PhD, Gigin Lin, MD, PhD, Christina Messiou, MD, MRCP, FRCR, Susan Lalondrelle, FRCR, Dow-Mu Koh, MD, FRCP, FRCR, Matthew David Blackledge, PhD |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
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| Series: | Advances in Radiation Oncology |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2452109425000338 |
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