Compact and ease-of-use quantitative phase microscopy for real-time live-cell imaging

Xin Shu; Yi Zhang; Mengxuan Niu; Wei Luo; Renjie Zhou

doi:10.1117/12.2610489

2 March 2022 Compact and ease-of-use quantitative phase microscopy for real-time live-cell imaging

Xin Shu, Yi Zhang, Mengxuan Niu, Wei Luo, Renjie Zhou

Proceedings Volume 11970, Quantitative Phase Imaging VIII; 1197004 (2022) https://doi.org/10.1117/12.2610489
Event: SPIE BiOS, 2022, San Francisco, California, United States

Abstract

Real-time quantitative phase imaging is beneficial for observation and analysis of living cells. Despite off-axis interferometry-based quantitative phase microscopy (off-axis QPM) offers single-shot image acquisition, it usually requires a calibration image captured at a blank field of view to correct the aberration and a multi-step processing algorithm to reconstruct a phase map. Therefore, it is challenging to achieve real-time phase imaging. To simplify experimental operations and expedite image processing, we propose a lightweight U-Net based deep neural network for calibration-free and fast phase retrieval in off-axis QPM. Output phase maps of the lightweight U-Net achieve high fidelity with an average Structural SIMilarity (SSIM) index value of 90.2%. Via running this lightweight U-Net model on a laptop connected with a portable QPM system, we demonstrate an ease-of-use and compact QPM method that can be used for real-time imaging of living cells.

Conference Presentation

Citation Download Citation

Xin Shu, Yi Zhang, Mengxuan Niu, Wei Luo, and Renjie Zhou "Compact and ease-of-use quantitative phase microscopy for real-time live-cell imaging", Proc. SPIE 11970, Quantitative Phase Imaging VIII, 1197004 (2 March 2022); https://doi.org/10.1117/12.2610489

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