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Frontiers of Information Technology & Electronic Engineering
ISSN 2095-9184 (print), ISSN 2095-9230 (online)
2017 Vol.18 No.9 P.1222-1235
Computational methods in super-resolution microscopy
Abstract: The broad applicability of super-resolution microscopy has been widely demonstrated in various areas and disciplines. The optimization and improvement of algorithms used in super-resolution microscopy are of great importance for achieving optimal quality of super-resolution imaging. In this review, we comprehensively discuss the computational methods in different types of super-resolution microscopy, including deconvolution microscopy, polarization-based super-resolution microscopy, structured illumination microscopy, image scanning microscopy, super-resolution optical fluctuation imaging microscopy, single-molecule localization microscopy, Bayesian super-resolution microscopy, stimulated emission depletion microscopy, and translation microscopy. The development of novel computational methods would greatly benefit super-resolution microscopy and lead to better resolution, improved accuracy, and faster image processing.
Key words: Super-resolution microscopy; Deconvolution; Computational methods
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DOI:
10.1631/FITEE.1601628
CLC number:
O436
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On-line Access:
2017-10-25
Received:
2016-10-14
Revision Accepted:
2016-12-13
Crosschecked:
2017-09-25