Rapid, artifact-reduced, image reconstruction for super-resolution structured illumination microscopy

Abstract

<title>Abstract</title> Super-resolution structured illumination microscopy (SR-SIM) is finding increasing application in biomedical research due to its superior capability to visualize the subcellular dynamics in living cells. However, during image reconstruction, the artifact problem, 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, the resulting JSFR-AR-SIM algorithm produces high-quality super-resolution images with minimal artifacts, and the reconstruction speed is increased by 600-fold, without compromising the spatial resolution. We expect this algorithm to facilitate SR-SIM as a routine tool in biomedical laboratories.