Automatic segmentation of uterine endometrial cancer on multi-sequence MRI using a convolutional neural network

Abstract Endometrial cancer (EC) is the most common gynecological tumor in developed countries, and preoperative risk stratification is essential for personalized medicine. There have been several radiomics studies for noninvasive risk stratification of EC using MRI. Although tumor segmentation is u...

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Bibliographic Details
Main Authors: Yasuhisa Kurata, Mizuho Nishio, Yusaku Moribata, Aki Kido, Yuki Himoto, Satoshi Otani, Koji Fujimoto, Masahiro Yakami, Sachiko Minamiguchi, Masaki Mandai, Yuji Nakamoto
Format: article
Language:EN
Published: Nature Portfolio 2021
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R
Q
Online Access:https://doaj.org/article/962db06ca6e14edf99d551abec3fc483
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