Head and neck automatic multi-organ segmentation on Dual-Energy Computed Tomography

Head and neck automatic multi-organ segmentation on Dual-Energy Computed Tomography

Background and purpose: Deep-learning-based automatic segmentation is widely used in radiation oncology to delineate organs-at-risk. Dual-energy CT (DECT) allows the reconstruction of enhanced contrast images that could help with manual and auto-delineation. This paper presents a performance evaluat...

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Bibliographic Details
Main Authors: Anh Thu Lê, Killian Sambourg, Roger Sun, Nicolas Deny, Vjona Cifliku, Rahimeh Rouhi, Eric Deutsch, Nathalie Fournier-Bidoz, Charlotte Robert
Format: Article
Language:English
Published: Elsevier 2024-10-01
Series:Physics and Imaging in Radiation Oncology
Subjects:
Dual-Energy Computed Tomography
Automatic segmentation
Multi-organ segmentation
Head-and-neck cancer
Virtual monoenergetic images
Online Access:http://www.sciencedirect.com/science/article/pii/S2405631624001246

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http://www.sciencedirect.com/science/article/pii/S2405631624001246

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