Open AccessA high-throughput technique to map cell images to cell positions using a 3D imaging flow cytometer
Author(s) -
Zunming Zhang,
Rui Tang,
Xinyu Chen,
Lauren Waller,
Alston Kau,
Anthony A. Fung,
Bien Gutierrez,
Cheolhong An,
Sung Hwan Cho,
Lingyan Shi,
YuHwa Lo
Publication year - 2022
Publication title -
proceedings of the national academy of sciences of the united states of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.2118068119
Subject(s) - computer science , throughput , fifo (computing and electronics) , artificial intelligence , computer vision , computer hardware , wireless , telecommunications
Significance This article demonstrates a high-throughput technique to map cell images to cell positions. The technology uses a three-dimensional (3D) imaging flow cytometer to record multiparameter 3D cell images at a throughput of 1,000 cells/s and a cell placement robot to place the exiting cells from the imaging system on a filter plate in a first-in–first-out manner so the cells on the plate have the same order as the cells that are imaged. Innovative algorithms were developed to match the cell sequences from the imaging and placement modules to detect and eliminate errors to ensure high accuracy. The technology forms an unprecedented bridge between single-cell molecular analysis and single-cell image analysis to connect phenotype and genotype analysis with single-cell resolution.