Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Image denoising for fluorescence microscopy by self-supervised transfer learning

Yina Wang, View ORCID ProfileHenry Pinkard, Emaad Khwaja, View ORCID ProfileShuqin Zhou, View ORCID ProfileLaura Waller, View ORCID ProfileBo Huang
doi: https://doi.org/10.1101/2021.02.01.429188
Yina Wang
1Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94143, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Henry Pinkard
2Computational Biology Graduate Group, University of California, Berkeley, CA 94720, USA
3Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
4Berkeley Institute for Data Science, Berkeley, CA 94720, USA
5University of California San Francisco Bakar Computational Health Sciences Institute, San Francisco, CA 94143, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Henry Pinkard
Emaad Khwaja
6UC Berkeley - UCSF Joint Graduate Program in Bioengineering, University of California, San Francisco, San Francisco, CA 94143, SUA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Shuqin Zhou
1Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94143, USA
7School of Pharmacy, Tsinghua University, Beijing, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Shuqin Zhou
Laura Waller
3Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA 94720, USA
4Berkeley Institute for Data Science, Berkeley, CA 94720, USA
8Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Laura Waller
Bo Huang
1Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94143, USA
8Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
9Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94143, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Bo Huang
  • For correspondence: bo.huang@ucsf.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

Abstract

When using fluorescent microscopy to study cellular dynamics, trade-offs typically have to be made between light exposure and quality of recorded image to balance phototoxicity and image signal-to-noise ratio. Image denoising is an important tool for retrieving information from dim live cell images. Recently, deep learning based image denoising is becoming the leading method because of its promising denoising performance, achieved by leveraging available prior knowledge about the noise model and samples at hand. We demonstrate that incorporating temporal information in the model can further improve the results. However, the practical application of this method has seen challenges because of the requirement of large, task-specific training datasets. In this work, addressed this challenge by combining self-supervised learning with transfer learning, which eliminated the demand of task-matched training data while maintaining denoising performance. We demonstrate its application in fluorescent imaging of different subcellular structures.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Text and figures are edited for clarity and a GitHub repository is set up for the code and test data.

  • https://github.com/BoHuangLab/Transfer-Learning-Denoising/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
Back to top
PreviousNext
Posted February 27, 2021.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Image denoising for fluorescence microscopy by self-supervised transfer learning
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Image denoising for fluorescence microscopy by self-supervised transfer learning
Yina Wang, Henry Pinkard, Emaad Khwaja, Shuqin Zhou, Laura Waller, Bo Huang
bioRxiv 2021.02.01.429188; doi: https://doi.org/10.1101/2021.02.01.429188
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Image denoising for fluorescence microscopy by self-supervised transfer learning
Yina Wang, Henry Pinkard, Emaad Khwaja, Shuqin Zhou, Laura Waller, Bo Huang
bioRxiv 2021.02.01.429188; doi: https://doi.org/10.1101/2021.02.01.429188

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (2653)
  • Biochemistry (5290)
  • Bioengineering (3699)
  • Bioinformatics (15839)
  • Biophysics (7287)
  • Cancer Biology (5649)
  • Cell Biology (8129)
  • Clinical Trials (138)
  • Developmental Biology (4789)
  • Ecology (7563)
  • Epidemiology (2059)
  • Evolutionary Biology (10618)
  • Genetics (7751)
  • Genomics (10175)
  • Immunology (5230)
  • Microbiology (13976)
  • Molecular Biology (5403)
  • Neuroscience (30909)
  • Paleontology (217)
  • Pathology (886)
  • Pharmacology and Toxicology (1527)
  • Physiology (2262)
  • Plant Biology (5041)
  • Scientific Communication and Education (1045)
  • Synthetic Biology (1400)
  • Systems Biology (4160)
  • Zoology (815)