Computational removal of background fluorescence for biological fluorescence microscopy

Hao Chih Lee, Ge Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Background fluorescence is a frequently encountered problem in biological fluorescence microscopy. It often significantly lowers the image signal-to-noise ratio and poses substantial challenges to subsequent computational image analysis. Here we propose a general computational method for separating and removing background fluorescence from a single fluorescence microscopy image. The method is formulated as solving a constrained convex optimization problem and assumes that the background signal is low-rank and additive to the sparse foreground signal. Solution of the optimization problem is found using a forward-backward algorithm. Our method only requires a single image and can be used in a broad range of biological fluorescence applications. We first validate performance of our method using synthetic image data. We then demonstrate applications of the method to actual biological image data.

Original languageEnglish
Title of host publication2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages205-208
Number of pages4
ISBN (Electronic)9781467319591
DOIs
StatePublished - 29 Jul 2014
Externally publishedYes
Event2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014 - Beijing, China
Duration: 29 Apr 20142 May 2014

Publication series

Name2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014

Conference

Conference2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014
Country/TerritoryChina
CityBeijing
Period29/04/142/05/14

Keywords

  • Background removal
  • Fluorescence microscopy
  • Kymograph
  • Low-rank approximation

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