Mandracchia, B. et al. Nat. Commun. 11, 94 (2020).

Scientific CMOS (sCMOS) cameras have quickly gained popularity among microscopists as these cameras offer fast, sensitive and high-resolution detection over a large field of view. However, sCMOS sensors have different sources of noise from those based on charged-coupled devices, and this noise can cause problems, especially for quantitative imaging. Mandracchia et al. have developed an algorithmic approach called automatic correction of sCMOS-related noise (ACsN) for reducing common noise sources. ACsN works by combining camera calibration, noise estimation and sparse filtering to correct relevant noise sources while preserving fine details of the image. The researchers show that their approach works with a variety of CMOS cameras. They also demonstrated improved results on biological samples imaged by several modalities, including widefield, light sheet, light field and localization microscopy.