Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer

Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer

Abstract Background Accurate and standardized descriptions of organs at risk (OARs) are essential in radiation therapy for treatment planning and evaluation. Traditionally, physicians have contoured patient images manually, which, is time-consuming and subject to inter-observer variability. This stu...

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Bibliographic Details
Main Authors: Sang Hee Ahn, Adam Unjin Yeo, Kwang Hyeon Kim, Chankyu Kim, Youngmoon Goh, Shinhaeng Cho, Se Byeong Lee, Young Kyung Lim, Haksoo Kim, Dongho Shin, Taeyoon Kim, Tae Hyun Kim, Sang Hee Youn, Eun Sang Oh, Jong Hwi Jeong
Format: Article
Language:English
Published: BMC 2019-11-01
Series:Radiation Oncology
Subjects:
Contouring
Atlas-based auto-segmentation
Deep-learning-based auto-segmentation
Deep convolution neural network (DCNN)
Online Access:http://link.springer.com/article/10.1186/s13014-019-1392-z

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http://link.springer.com/article/10.1186/s13014-019-1392-z

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