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Apr, 2018
StainGAN：数字组织学图像染色风格转移
StainGAN: Stain Style Transfer for Digital Histological Images
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M Tarek Shaban, Christoph Baur, Nassir Navab, Shadi Albarqouni
TL;DR
利用深度学习方法的CycleGANs，不需要专家选择代表性的参考标本，解决了数字化组织学诊断中由于多种因素引起的染色剂颜色变化引起的难题，并在乳腺癌肿瘤分类等临床应用中得到了验证。
Abstract
digitized histological diagnosis
is in increasing demand. However, color variations due to various factors are imposing obstacles to the diagnosis process. The problem of
stain color variations
is a well-defined
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