Fourier-domain-compressed optical time-stretch quantitative phase imaging flow cytometry

被引:0
|
作者
Li, Rubing [1 ]
Weng, Yueyun [1 ,2 ]
Wei, Shubin [1 ]
Lin, Siyuan [1 ]
Huang, Jin [1 ]
Song, Congkuan [3 ]
Shen, Hui [4 ]
Hou, Jinxuan [5 ]
Xu, Yu [6 ]
Mei, Liye [1 ,7 ]
Wang, Du [1 ]
Zou, Yujie [8 ]
Yin, Tailang [8 ]
Zhou, Fuling [4 ]
Geng, Qing [3 ]
Liu, Sheng [1 ,2 ]
Lei, Cheng [1 ,9 ,10 ]
机构
[1] Wuhan Univ, Inst Technol Sci, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Sch Power & Mech Engn, Wuhan 430072, Peoples R China
[3] Wuhan Univ, Renmin Hosp, Dept Thorac Surg, Wuhan 430060, Peoples R China
[4] Wuhan Univ, Zhongnan Hosp, Dept Hematol, Wuhan 430071, Peoples R China
[5] Wuhan Univ, Zhongnan Hosp, Dept Thyroid & Breast Surg, Wuhan 430071, Peoples R China
[6] Wuhan Univ, Zhongnan Hosp, Dept Radiat & Med Oncol, Wuhan 430071, Peoples R China
[7] Hubei Univ Technol, Sch Comp Sci, Wuhan 430068, Peoples R China
[8] Wuhan Univ, Renmin Hosp, Reprod Med Ctr, Wuhan 430060, Peoples R China
[9] Wuhan Univ, Suzhou Inst, Suzhou 215000, Peoples R China
[10] Wuhan Univ, Shenzhen Inst, Shenzhen 518057, Peoples R China
关键词
HIGH-THROUGHPUT; CELL;
D O I
10.1364/PRJ.523653
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Optical time-stretch (OTS) imaging flow cytometry offers a promising solution for high-throughput and highprecision cell analysis due to its capabilities of high-speed, high-quality, and continuous imaging. Compressed sensing (CS) makes it practically applicable by significantly reducing the data volume while maintaining its highspeed and high-quality imaging properties. To enrich the information of the images acquired with CS-equipped OTS imaging flow cytometry, in this work we propose and experimentally demonstrate Fourier-domain- compressed OTS quantitative phase imaging flow cytometry. It is capable of acquiring intensity and quantitative phase images of cells simultaneously from the compressed data. To evaluate the performance of our method, static microparticles and a corn root cross section are experimentally measured under various compression ratios. Furthermore, to show how our method can be applied in practice, we utilize it in the drug response analysis of breast cancer cells. Experimental results show that our method can acquire high-quality intensity and quantitative phase images of flowing cells at a flowing speed of 1 m/s and a compression ratio of 30%. Combined with machine-learning-based image analysis, it can distinguish drug-treated and drug-untreated cells with an accuracy of over 95%. We believe our method can facilitate cell analysis in both scientific research and clinical settings where both high-throughput and high-content cell analysis is required. (c) 2024 Chinese Laser Press
引用
收藏
页码:1627 / 1639
页数:13
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