Image reconstruction for structured-illumination microscopy with low signal level

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

作者机构：Univ Calif Davis Ctr Biophoton Sacramento CA 95817 USA Univ Melbourne Melbourne Vic 3010 Australia Appl Precis Issaquah WA 98027 USA Univ Calif Davis Dept Pathol & Lab Med Sacramento CA 95817 USA 

出 版 物：《OPTICS EXPRESS》 (Opt. Express)

年 卷 期：2014年第22卷第7期

页      面：8687-8702页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 0702[理学-物理学] 

基　　金：NSF Partnerships for Innovation: Accelerating Innovation Research Div Of Industrial Innovation & Partnersh Directorate For Engineering Funding Source: National Science Foundation 

主　　题：Illumination design Image processing algorithms Image quality Image reconstruction Optical transfer functions Spatial light modulators 

摘      要：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. (C) 2014 Optical Society of America