@article {23329,
	title = {Computational methods in super-resolution microscopy},
	journal = {Frontiers of Information Technology \&amp; Electronic Engineering},
	volume = {18},
	year = {2017},
	note = {Fl2djTimes Cited:3Cited References Count:57},
	month = {Sep},
	pages = {1222-1235},
	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.},
	keywords = {breaking},
	isbn = {2095-9184},
	doi = {10.1631/Fitee.1601628},
	url = {\&lt;Go to ISI\&gt;://WOS:000414024600003},
	author = {Zeng, Z. P. and Xie, H. and L. Chen and Zhanghao, K. and Zhao, K. and Yang, X. S. and Xi, P.}
}
