A Novel U-Like Network For The Segmentation Of Thoracic Organs

Accurate segmentation of organs at risk (OARs) in computed tomography (CT) is an essential step in radiation therapy for thoracic cancer treatment. However, the manual segmentation of OARs is time-consuming and subject to inter-observer variation. In this paper, we propose a novel U-like deep convol...

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Bibliographic Details

Published in:	2020 IEEE 17th International Symposium on Biomedical Imaging Workshops (ISBI Workshops) pp. 1 - 4
Main Authors:	Shi, Jun, Wen, Ke, Hao, Xiaoyu, Xue, Xudong, An, Hong, Zhang, Hongyan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.04.2020
Subjects:	Biomedical imaging Computed tomography Convolution convolutional neural network (CNN) Decoding hybrid dilated convolution Image segmentation Lung multi-task learning OARs segmentation radiation therapy Two dimensional displays
Online Access:	Get full text
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