Image reconstruction for structured-illumination microscopy with low signal level

Kaiqin Chu; Paul J. McMillan; Zachary J. Smith; Jie Yin; Jeniffer Atkins; Paul Goodwin; Sebastian Wachsmann-Hogiu; Stephen Lane

doi:10.1364/OE.22.008687

Image reconstruction for structured-illumination microscopy with low signal level

Kaiqin Chu, Paul J. McMillan, Zachary J. Smith, Jie Yin, Jeniffer Atkins, Paul Goodwin, Sebastian Wachsmann-Hogiu, Stephen Lane

Pathology and Laboratory Medicine

Research output: Contribution to journal › Article › peer-review

19 Scopus citations

Abstract

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 prefiltering 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.

Original language	English (US)
Pages (from-to)	8687-8702
Number of pages	16
Journal	Optics Express
Volume	22
Issue number	7
DOIs	https://doi.org/10.1364/OE.22.008687
State	Published - 2014

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics

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AU - Goodwin, Paul

AU - Wachsmann-Hogiu, Sebastian

AU - Lane, Stephen

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