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Unsupervised content-preserving transformation for optical microscopy

Xinyang Li Hao Xie Haoqian Wang Qionghai Dai Guoxun Zhang Hui Qiao Feng Bao Yue Deng Jiamin Wu Yangfan He Jingping Yun Xing Lin

光：科学与应用（英文版）2021，Vol.10Issue(3)：390-400,11.

Unsupervised content-preserving transformation for optical microscopy

Xinyang Li ¹Hao Xie ²Haoqian Wang ³Qionghai Dai ¹Guoxun Zhang ³Hui Qiao ²Feng Bao ³Yue Deng ¹Jiamin Wu ³Yangfan He ¹Jingping Yun ³Xing Lin¹

作者信息

1. Department of Automation,Tsinghua University,Beijing 100084,China
2. Tsinghua Shenzhen International Graduate School,Tsinghua University,Shenzhen 518055,China
3. Institute for Brain and Cognitive Sciences,Tsinghua University,Beijing 100084,China
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摘要

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Xinyang Li,Hao Xie,Haoqian Wang,Qionghai Dai,Guoxun Zhang,Hui Qiao,Feng Bao,Yue Deng,Jiamin Wu,Yangfan He,Jingping Yun,Xing Lin..Unsupervised content-preserving transformation for optical microscopy[J].光：科学与应用（英文版）,2021,10(3):390-400,11.

基金项目

We would like to acknowledge Weigert et al.for making their source code and data related to image restoration openly available to the community.We thank the Rubin Lab at Harvard,the Finkbeiner Lab at Gladstone,and GoogleAccelerated Science for releasing their datasets on virtual cell staining.We thank Jingjing Wang,affiliated with the apparatus sharing platform of Tsinghua University,for assistance with the imaging of histopathology slides.This work was supported by the National Natural Science Foundation of China(62088102,61831014,62071271,and 62071272),Projects of MOST(2020AA0105500 and 2020AAA0130000),Shenzhen Science and Technology Projects(ZDYBH201900000002 and JCYJ20180508152042002),and the National Postdoctoral Program for Innovative Talents(BX20190173). （62088102,61831014,62071271,and 62071272）

光：科学与应用（英文版）

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ISSN：2095-5545

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