Compressive confocal microscopy imaging at the single-photon level with ultra-low sampling ratios

Abstract

Laser-scanning confocal microscopy serves as a critical instrument for microscopic research in biology. However, it suffers from low imaging speed and high phototoxicity. Here we build a novel deep compressive confocal microscope, which employs a digital micromirror device as a coding mask for single-pixel imaging and a pinhole for confocal microscopic imaging respectively. Combined with a deep learning reconstruction algorithm, our system is able to achieve high-quality confocal microscopic imaging with low phototoxicity. Our imaging experiments with fluorescent microspheres demonstrate its capability of achieving single-pixel confocal imaging with a sampling ratio of only approximately 0.03% in specific sparse scenarios. Moreover, the deep compressive confocal microscope allows single-pixel imaging at the single-photon level, thus reducing the excitation light power requirement for confocal imaging and suppressing the phototoxicity. We believe that our system has great potential for long-duration and high-speed microscopic imaging of living cells. Shuai Liu, Bin Chen and colleagues improve imaging speed and reduced phototoxicity in confocal microimaging by building a deep compressive confocal microscope. Digital micromirror acts as a coding mask for deep learning-based reconstruction algorithms.