Rectal cancer: Toward fully automatic discrimination of T2 and T3 rectal cancers using deep convolutional neural network-Reference-Cited by-同舟云学术

Rectal cancer: Toward fully automatic discrimination of T2 and T3 rectal cancers using deep convolutional neural network

Published:2019-02-19 Issue:3 Volume:29 Page:247-259
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Technol

Author:

Kim Jongin¹,Oh Ji Eun²,Lee Joohyung²,Kim Min Ju³,Hur Bo Yun³,Sohn Dae Kyung²³,Lee Boreom¹^ORCID

Affiliation:

1. Department of Biomedical Science and Engineering (BMSE); Institute of Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST); Gwangju Republic of Korea

2. Innovative Medical Engineering and Technology, Division of Convergence Technology; Research Institute and Hospital, National Cancer Center; Goyang Republic of Korea

3. Center for Colorectal Cancer; Research Institute and Hospital, National Cancer Center; Goyang Republic of Korea

Funder

Gwangju Institute of Science and Technology

National Cancer Center

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/ima.22311/fullpdf

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5. Restaging of rectal cancer with MR imaging after concurrent chemotherapy and radiation therapy;Kim;Radiographics,2010

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