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Auto-segmentation of head and neck organs at risk in radiotherapy and its dependence on anatomic similarity |
Anantharaman Ayyalusamy, Subramani Vellaiyan, Shanmuga Subramanian, Arivarasan Ilamurugu, Shyama Satpathy, Mohammed Nauman, Gowtham Katta, Aneesha Madineni |
Radiation Oncology Journal. 2019;37(2):134-142. Published online 2019 June 30 DOI: https://doi.org/10.3857/roj.2019.00038 |
Auto-segmentation of head and neck organs at risk in radiotherapy and its dependence on anatomic similarity 1554 poster EVALUATION OF A COMMERCIAL AUTO-SEGMENTATION TOOL IN THE OUTLINING OF LYMPH NODES & ORGANS AT RISK IN HEAD AND NECK CANCER Auto‐segmentation of organs at risk for head and neck radiotherapy planning: From atlas‐based to deep learning methods PD-0868 Comparison of segmentation algorithms for organs at risk delineation on head-and-neck CT images PH-0604: The impact of training sample size on deep learning based organ auto segmentation for head neck PD-0416: Robust feature auto-segmentation of head and neck cancer Development of a Deep Learning-Based Auto-Segmentation of Organs at Risk for Head and Neck Radiotherapy Planning Identifying patients who may benefit from adaptive radiotherapy: Does the literature on anatomic and dosimetric changes in head and neck organs at risk during radiotherapy provide information to help? PD-0313 A comparison of multiple deep learning-based auto-segmentation systems for head and neck cancer Systematic Study of Patient-Specific Organs at Risk Auto-Segmentation on Daily kVCT Images for Adaptive Head and Neck Radiotherapy |
This metadata service is kindly provided by CrossRef from May 29, 2014. Radiat Oncol J has participated in CrossRef Text and Data Mining service since October 29, 2014. |