Intelligent Phase Contrast Meta-Microscope System

• Published in: Nano letters Vol. 23; no. 24; pp. 11630 - 11637
• Main Authors: Chu, Cheng Hung, Chia, Yu-Hsin, Hsu, Hung-Chuan, Vyas, Sunil, Tsai, Chen-Ming, Yamaguchi, Takeshi, Tanaka, Takuo, Chen, Huei-Wen, Luo, Yuan, Yang, Pan-Chyr, Tsai, Din Ping
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 27.12.2023
• Subjects: Humans; Microscopy - methods; Microscopy, Phase-Contrast - methods; Optical Devices; Optical Imaging; deep learning; edge detection; phase contrast imaging; metasurface
• ISSN: 1530-6984; 1530-6992; 1530-6992
• DOI: 10.1021/acs.nanolett.3c03484

Phase contrast imaging techniques enable the visualization of disparities in the refractive index among various materials. However, these techniques usually come with a cost: the need for bulky, inflexible, and complicated configurations. Here, we propose and experimentally demonstrate an ultracompact meta-microscope, a novel imaging platform designed to accomplish both optical and digital phase contrast imaging. The optical phase contrast imaging system is composed of a pair of metalenses and an intermediate spiral phase metasurface located at the Fourier plane. The performance of the system in generating edge-enhanced images is validated by imaging a variety of human cells, including lung cell lines BEAS-2B, CLY1, and H1299 and other types. Additionally, we integrate the ResNet deep learning model into the meta-microscope to transform bright-field images into edge-enhanced images with high contrast accuracy. This technology promises to aid in the development of innovative miniature optical systems for biomedical and clinical applications.