Computational methods in super-resolution microscopy

作者：Zhiping Zeng, Hao Xie, Long Chen, Karl Zhanghao, Kun Zhao, Xusan Yang, Peng Xi · 发表于：Frontiers of Information Technology & Electronic Engineering · 年份：2017 · DOI：10.1631/fitee.1601628 · 被引用次数：20 · 研究领域：Advanced Fluorescence Microscopy Techniques、Optical Coherence Tomography Applications、Photoacoustic and Ultrasonic Imaging

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.