Structured illumination microscopy with unknown patterns and a statistical prior
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Citation (published version)Li-Hao Yeh, Lei Tian, Laura Waller. 2017. "Structured illumination microscopy with unknown patterns and a statistical prior.." Biomed Opt Express, Volume 8, Issue 2, pp. 695 - 711.
Structured illumination microscopy (SIM) improves resolution by down-modulating high-frequency information of an object to fit within the passband of the optical system. Generally, the reconstruction process requires prior knowledge of the illumination patterns, which implies a well-calibrated and aberration-free system. Here, we propose a new algorithmic self-calibration strategy for SIM that does not need to know the exact patterns a priori, but only their covariance. The algorithm, termed PE-SIMS, includes a pattern-estimation (PE) step requiring the uniformity of the sum of the illumination patterns and a SIM reconstruction procedure using a statistical prior (SIMS). Additionally, we perform a pixel reassignment process (SIMS-PR) to enhance the reconstruction quality. We achieve 2× better resolution than a conventional widefield microscope, while remaining insensitive to aberration-induced pattern distortion and robust against parameter tuning.
RightsCopyright 2016 Optical Society of America. The accepted manuscript of this article is being made available in OpenBU under Boston University's open access policy.