Fast and accurate sCMOS noise correction for fluorescence microscopy

Biagio Mandracchia, Xuanwen Hua, Changliang Guo, Jeonghwan Son, Tara Urner and Shu Jia ()
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Biagio Mandracchia: Georgia Institute of Technology and Emory University
Xuanwen Hua: Georgia Institute of Technology and Emory University
Changliang Guo: Georgia Institute of Technology and Emory University
Jeonghwan Son: Georgia Institute of Technology and Emory University
Tara Urner: Georgia Institute of Technology and Emory University
Shu Jia: Georgia Institute of Technology and Emory University

Nature Communications, 2020, vol. 11, issue 1, 1-12

Abstract: Abstract The rapid development of scientific CMOS (sCMOS) technology has greatly advanced optical microscopy for biomedical research with superior sensitivity, resolution, field-of-view, and frame rates. However, for sCMOS sensors, the parallel charge-voltage conversion and different responsivity at each pixel induces extra readout and pattern noise compared to charge-coupled devices (CCD) and electron-multiplying CCD (EM-CCD) sensors. This can produce artifacts, deteriorate imaging capability, and hinder quantification of fluorescent signals, thereby compromising strategies to reduce photo-damage to live samples. Here, we propose a content-adaptive algorithm for the automatic correction of sCMOS-related noise (ACsN) for fluorescence microscopy. ACsN combines camera physics and layered sparse filtering to significantly reduce the most relevant noise sources in a sCMOS sensor while preserving the fine details of the signal. The method improves the camera performance, enabling fast, low-light and quantitative optical microscopy with video-rate denoising for a broad range of imaging conditions and modalities.

Date: 2020
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DOI: 10.1038/s41467-019-13841-8

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