<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zeng, Z. P.</style></author><author><style face="normal" font="default" size="100%">Xie, H.</style></author><author><style face="normal" font="default" size="100%">L. Chen</style></author><author><style face="normal" font="default" size="100%">Zhanghao, K.</style></author><author><style face="normal" font="default" size="100%">Zhao, K.</style></author><author><style face="normal" font="default" size="100%">Yang, X. S.</style></author><author><style face="normal" font="default" size="100%">Xi, P.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Computational methods in super-resolution microscopy</style></title><secondary-title><style face="normal" font="default" size="100%">Frontiers of Information Technology &amp;amp; Electronic Engineering</style></secondary-title><short-title><style face="normal" font="default" size="100%">Computational methods in super-resolution microscopy</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">breaking</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">Sep</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">&amp;lt;Go to ISI&amp;gt;://WOS:000414024600003</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">1222-1235</style></pages><isbn><style face="normal" font="default" size="100%">2095-9184</style></isbn><language><style face="normal" font="default" size="100%">English</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract><issue><style face="normal" font="default" size="100%">9</style></issue><accession-num><style face="normal" font="default" size="100%">WOS:000414024600003</style></accession-num><notes><style face="normal" font="default" size="100%">Fl2djTimes Cited:3Cited References Count:57</style></notes></record></records></xml>