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- Title
Photon-free (s)CMOS camera characterization for artifact reduction in high- and super-resolution microscopy.
- Authors
Diekmann, Robin; Deschamps, Joran; Li, Yiming; Deguchi, Takahiro; Tschanz, Aline; Kahnwald, Maurice; Matti, Ulf; Ries, Jonas
- Abstract
Modern implementations of widefield fluorescence microscopy often rely on sCMOS cameras, but this camera architecture inherently features pixel-to-pixel variations. Such variations lead to image artifacts and render quantitative image interpretation difficult. Although a variety of algorithmic corrections exists, they require a thorough characterization of the camera, which typically is not easy to access or perform. Here, we developed a fully automated pipeline for camera characterization based solely on thermally generated signal, and implemented it in the popular open-source software Micro-Manager and ImageJ/Fiji. Besides supplying the conventional camera maps of noise, offset and gain, our pipeline also gives access to dark current and thermal noise as functions of the exposure time. This allowed us to avoid structural bias in single-molecule localization microscopy (SMLM), which without correction is substantial even for scientific-grade, cooled cameras. In addition, our approach enables high-quality 3D super-resolution as well as live-cell time-lapse microscopy with cheap, industry-grade cameras. As our approach for camera characterization does not require any user interventions or additional hardware implementations, numerous correction algorithms that rely on camera characterization become easily applicable. Pixel-to-pixel variations in sCMOS cameras lead to image artifacts in widefield fluorescence microscopy, and algorithmic corrections require thorough camera characterization. Here, the authors present an open source automated pipeline for camera characterization based solely on thermally generated signal.
- Subjects
IMAGE analysis; MICROSCOPY; THERMAL noise; FLUORESCENCE microscopy; CAMERAS; DIGITAL cameras
- Publication
Nature Communications, 2022, Vol 13, Issue 1, p1
- ISSN
2041-1723
- Publication type
Article
- DOI
10.1038/s41467-022-30907-2