AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy
Abstract
Radiation therapy (RT) is a common treatment option for head and neck (HaN) cancer. An important step involved in RT planning is the delineation of organs-at-risks (OARs) based on HaN computed tomography (CT). However, manually delineating OARs is time-consuming as each slice of CT images needs to be individually examined and a typical CT consists of hundreds of slices. Automating OARs segmentation has the benefit of both reducing the time and...
Paper Details
Title
AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy
Published Date
Dec 17, 2018
Journal
Volume
46
Issue
2
Pages
576 - 589
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