Open AccessImage reconstruction for structured-illumination microscopy with low signal level
Author(s) -
Kaiqin Chu,
Paul J. McMillan,
Zachary J. Smith,
Jie Yin,
Jeniffer Atkins,
Paul C. Goodwin,
Sebastian WachsmannHogiu,
Stephen M. Lane
Publication year - 2014
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.22.008687
Subject(s) - photobleaching , optics , microscopy , image quality , image processing , image restoration , artificial intelligence , computer vision , computer science , iterative reconstruction , digital image processing , materials science , hyperspectral imaging , image (mathematics) , physics , fluorescence
We report a new image processing technique for the structured illumination microscopy designed to work with low signals, with the goal of reducing photobleaching and phototoxicity of the sample. Using a pre-filtering process to estimate experimental parameters and total variation as a constraint to reconstruct, we obtain two orders of magnitude of exposure reduction while maintaining the resolution improvement and image quality compared to a standard structured illumination microscopy. The algorithm is validated on both fixed and live cell data with results confirming that we can image more than 15x more time points compared to the standard technique.