19 July 2016 Structural anisotropy quantification improves the final superresolution image of localization microscopy
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Abstract
Superresolution localization microscopy initially produces a dataset of fluorophore coordinates instead of a conventional digital image. Therefore, superresolution localization microscopy requires additional data analysis to present a final superresolution image. However, methods of employing the structural information within the localization dataset to improve the data analysis performance remain poorly developed. Here, we quantify the structural information in a localization dataset using structural anisotropy, and propose to use it as a figure of merit for localization event filtering. With simulated as well as experimental data of a biological specimen, we demonstrate that exploring structural anisotropy has allowed us to obtain superresolution images with a much cleaner background.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
Yina Wang, Zhen-li Huang, "Structural anisotropy quantification improves the final superresolution image of localization microscopy," Journal of Biomedical Optics 21(7), 076011 (19 July 2016). https://doi.org/10.1117/1.JBO.21.7.076011 . Submission:
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