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DeepS: a web server for image optical sectioning and super resolution microscopy based on a deep learning framework.

Authors :
Zhu, Qingjie
Shao, Yi
Wang, Zhicheng
Chen, Xingjun
Li, Chunqiong
Liang, Zihan
Jia, Mingyue
Guo, Qingchun
Zhao, Hu
Kong, Lei
Zhang, Li
Source :
Bioinformatics. Sep2021, Vol. 37 Issue 18, p3086-3087. 2p.
Publication Year :
2021

Abstract

Motivation Microscopy technology plays important roles in many biological research fields. Solvent-cleared brain high-resolution (HR) 3D image reconstruction is an important microscopy application. However, 3D microscopy image generation is time-consuming and expensive. Therefore, we have developed a deep learning framework (DeepS) for both image optical sectioning and super resolution microscopy. Results Using DeepS to perform super resolution solvent-cleared mouse brain microscopy 3D image yields improved performance in comparison with the standard image processing workflow. We have also developed a web server to allow online usage of DeepS. Users can train their own models with only one pair of training images using the transfer learning function of the web server. Availabilityand implementation http://deeps.cibr.ac.cn. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13674803
Volume :
37
Issue :
18
Database :
Academic Search Index
Journal :
Bioinformatics
Publication Type :
Academic Journal
Accession number :
152770354
Full Text :
https://doi.org/10.1093/bioinformatics/btab144