Research Papers: Imaging

Structural anisotropy quantification improves the final superresolution image of localization microscopy

[+] Author Affiliations
Yina Wang, Zhen-li Huang

Huazhong University of Science and Technology-Wuhan National Laboratory for Optoelectronics, Britton Chance Center for Biomedical Photonics, 1037 Luoyu Road, Wuhan 430074, China

Huazhong University of Science and Technology, Key Laboratory of Biomedical Photonics of Ministry of Education, Department of Biomedical Engineering, 1037 Luoyu Road, Wuhan 430074, China

J. Biomed. Opt. 21(7), 076011 (Jul 19, 2016). doi:10.1117/1.JBO.21.7.076011
History: Received May 22, 2016; Accepted July 6, 2016
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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.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Yina Wang and Zhen-li Huang
"Structural anisotropy quantification improves the final superresolution image of localization microscopy", J. Biomed. Opt. 21(7), 076011 (Jul 19, 2016). ; http://dx.doi.org/10.1117/1.JBO.21.7.076011


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