Open AccessStructured illumination microscopy with noise-controlled image reconstructions
Author(s) -
Carlas Smith,
Johan A. Slotman,
Lothar Schermelleh,
Nadya Chakrova,
Sangeetha Hari,
Yoram Vos,
C. W. Hagen,
Marcel Müller,
Wiggert van Cappellen,
Adriaan B. Houtsmuller,
Jacob P. Hoogenboom,
Sjoerd Stallinga
Publication year - 2021
Publication title -
nature methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 19.469
H-Index - 318
eISSN - 1548-7105
pISSN - 1548-7091
DOI - 10.1038/s41592-021-01167-7
Subject(s) - noise (video) , computer science , computer vision , background noise , noise floor , artificial intelligence , microscopy , iterative reconstruction , algorithm , noise measurement , optics , noise reduction , physics , image (mathematics) , telecommunications
Super-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artifacts that limit their applicability for lower signal-to-noise data. Here we present a physically realistic noise model that explains the structured noise artifact, which we then use to motivate new complementary reconstruction approaches. True-Wiener-filtered SIM optimizes contrast given the available signal-to-noise ratio, and flat-noise SIM fully overcomes the structured noise artifact while maintaining resolving power. Both methods eliminate ad hoc user-adjustable reconstruction parameters in favor of physical parameters, enhancing objectivity. The new reconstructions point to a trade-off between contrast and a natural noise appearance. This trade-off can be partly overcome by further notch filtering but at the expense of a decrease in signal-to-noise ratio. The benefits of the proposed approaches are demonstrated on focal adhesion and tubulin samples in two and three dimensions, and on nanofabricated fluorescent test patterns.