Robust imaging flow cytometer based on in-silico optofluidic time-stretch imaging with assistance of optical phase

Shu Chen; Haochen Yan; Shibo Gao; Ting-Hui Xiao; Chong-Xin Shan

doi:10.1016/j.talanta.2025.128503

Robust imaging flow cytometer based on in-silico optofluidic time-stretch imaging with assistance of optical phase

Talanta. 2025 Jun 21:296:128503. doi: 10.1016/j.talanta.2025.128503. Online ahead of print.

Authors

Shu Chen¹, Haochen Yan², Shibo Gao¹, Ting-Hui Xiao³, Chong-Xin Shan⁴

Affiliations

¹ Laboratory of Zhongyuan Light, School of Physics, Zhengzhou University, Zhengzhou, 450001, China; Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, Key Laboratory of Materials Physics, Ministry of Education, School of Physics, Zhengzhou University, Zhengzhou, 450001, China.
² Max Planck Institute, Science of Light, Erlangen, Bavaria, Germany; Department of Chemistry, School of Science, The University of Tokyo, Tokyo, Japan.
³ Laboratory of Zhongyuan Light, School of Physics, Zhengzhou University, Zhengzhou, 450001, China; Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, Key Laboratory of Materials Physics, Ministry of Education, School of Physics, Zhengzhou University, Zhengzhou, 450001, China; Institute of Quantum Materials and Physics, Henan Academy of Sciences, Zhengzhou, China; Department of Chemistry, School of Science, The University of Tokyo, Tokyo, Japan. Electronic address: xiaoth@zzu.edu.cn.
⁴ Henan Key Laboratory of Diamond Optoelectronic Materials and Devices, Key Laboratory of Materials Physics, Ministry of Education, School of Physics, Zhengzhou University, Zhengzhou, 450001, China.

PMID: 40561805
DOI: 10.1016/j.talanta.2025.128503

Abstract

Imaging flow cytometry is a widely used technique for high-throughput, label-free single-cell analysis. However, its effectiveness is often compromised by experimental perturbations, such as random defocusing and off-axis light coupling, which degrade image quality and hinder reliable analysis. In this study, we present a robust imaging flow cytometer based on in-silico optofluidic time-stretch imaging with the assistance of optical phase. We employ a generative adversarial network (GAN) trained on paired bright-field and phase images to effectively mitigate perturbation-induced artifacts. Experimental results demonstrate a ∼67 % improvement in cell classification accuracy, illustrating the enhanced robustness of the system. This approach offers a scalable and reliable method for improving the performance and accuracy of high-throughput single-cell imaging systems.

Keywords: Cell classification; Imaging flow cytometry; Optofluidic time-stretch imaging.