2D and 3D structured illumination microscopy with unknown patterns and a statistical prior
July 23-26, 2017
Structured illumination microscopy (SIM) is one of the most widely applied super-resolution microscopy techniques in bioimaging. It improves resolution by down-modulating a sample’s high spatial frequency information to fit within the passband of the optical system. Normally, the reconstruction process requires prior knowledge of the illumination patterns. Aberrations from the optical system or from the sample itself will distort the patterns and degrade performance. Here, we propose a new algorithmic self-calibration strategy for both 2D and 3D 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). We achieve 2x better resolution than a conventional widefield microscope, without needing to know the illumination patterns and while remaining insensitive to aberration-induced pattern distortion.
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Li-Hao Yeh and Laura Waller, "2D and 3D structured illumination microscopy with unknown patterns and a statistical prior" in "Advances in Optics for Biotechnology, Medicine and Surgery XV", Peter So, Massachusetts Institute of Technology, USA Kate Bechtel, Triple Ring Technologies, USA Ivo Vellekoop, University of Twente, The Netherlands Michael Choma, Yale University, USA Eds, ECI Symposium Series, (2017). http://dc.engconfintl.org/biotech_med_xv/13
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