Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy
Zhaojun Wang, Tianyu Zhao, Yan-an Cai, Jingxiang Zhang, Huiwen Hao, Yansheng Liang, Shaowei Wang, Yujie Sun, Tongsheng Chen, Piero R. Bianco, Kwangsung Oh, Ming Lei
Abstract
Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells. However, during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures, limits this technique from becoming a routine imaging tool for biologists. To address these issues, an accelerated, artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm (JSFR-AR-SIM) was developed by integrating a high-speed reconstruction framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact. Consequently, JSFR-AR-SIM produces high-quality, super-resolution images with minimal artifacts, and the reconstruction speed is increased. We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories.