Optimal sparsity allows reliable system-aware restoration of fluorescence microscopy images

Author:

Mandracchia Biagio123ORCID,Liu Wenhao1,Hua Xuanwen1ORCID,Forghani Parvin4ORCID,Lee Soojung1ORCID,Hou Jessica5ORCID,Nie Shuyi56ORCID,Xu Chunhui46ORCID,Jia Shu16ORCID

Affiliation:

1. Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.

2. Scientific-Technical Central Units, Instituto de Salud Carlos III (ISCIII), Majadahonda, Spain.

3. ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain.

4. Department of Pediatrics, School of Medicine, Emory University, Atlanta, GA, USA.

5. School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.

6. Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, USA.

Abstract

Fluorescence microscopy is one of the most indispensable and informative driving forces for biological research, but the extent of observable biological phenomena is essentially determined by the content and quality of the acquired images. To address the different noise sources that can degrade these images, we introduce an algorithm for multiscale image restoration through optimally sparse representation (MIRO). MIRO is a deterministic framework that models the acquisition process and uses pixelwise noise correction to improve image quality. Our study demonstrates that this approach yields a remarkable restoration of the fluorescence signal for a wide range of microscopy systems, regardless of the detector used (e.g., electron-multiplying charge-coupled device, scientific complementary metal-oxide semiconductor, or photomultiplier tube). MIRO improves current imaging capabilities, enabling fast, low-light optical microscopy, accurate image analysis, and robust machine intelligence when integrated with deep neural networks. This expands the range of biological knowledge that can be obtained from fluorescence microscopy.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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