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Journal article

Esophagus segmentation from planning CT images using an atlas-based deep learning approach

Abstract:

Background and Objective: One of the main steps in the planning of radiotherapy (RT) is the segmentation of organs at risk (OARs) in Computed Tomography (CT). The esophagus is one of the most difficult OARs to segment. The boundaries between the esophagus and other surrounding tissues are not well-defined, and it is presented in several slices of the CT. Thus, manually segment the esophagus requires a lot of experience and takes time. This difficulty in manual segmentation...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.cmpb.2020.105685

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Institution:
University of Oxford
Division:
MSD
Department:
Women's & Reproductive Health
Role:
Author
Publisher:
Elsevier
Journal:
Computer Methods and Programs in Biomedicine More from this journal
Volume:
197
Article number:
105685
Publication date:
2020-08-07
Acceptance date:
2020-07-28
DOI:
ISSN:
0169-2607
Language:
English
Keywords:
Pubs id:
1123915
Local pid:
pubs:1123915
Deposit date:
2020-08-06

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