Recent Advances in Structured Illumination Microscopy: From Fundamental Principles to AI-Enhanced Imaging

Abstract

Structured illumination microscopy (SIM) has emerged as a pivotal super-resolution technique in biological imaging. This review aims to introduce the fundamental principles of SIM, primarily focuses on the latest developments in super-resolution SIM imaging, such as the light illumination and modulation devices, and the image reconstruction algorithms. Additionally, the application of deep learning (DL) technology in SIM imaging is explored, which is employed to enhance image quality, accelerate imaging and reconstruction speed or replace the current image reconstruction method. Furthermore, the key evaluation metrics are proposed and discussed for assessment of deep-learning neural networks, especially for their employment in SIM. Finally, the future integration of artificial intelligence (AI) with SIM system and the perspective of smart microscope are also discussed.