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Label-free image-encoded microfluidic cell sorter with a scanning Bessel beam
Author(s) -
Xinyu Chen,
Lauren Waller,
Jiajie Chen,
Rui Tang,
Zunming Zhang,
Ivan Gagne,
Bien Gutierrez,
Sung Hwan Cho,
Chi-Yang Tseng,
Ian Lian,
YuHwa Lo
Publication year - 2021
Publication title -
apl photonics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.094
H-Index - 34
ISSN - 2378-0967
DOI - 10.1063/5.0051354
Subject(s) - optics , sorting , microfluidics , waveform , artificial intelligence , gaussian , materials science , computer science , physics , nanotechnology , algorithm , telecommunications , radar , quantum mechanics
The microfluidic-based, label-free image-guided cell sorter offers a low-cost, high information content, and disposable solution that overcomes many limitations in conventional cell sorters. However, flow confinement for most microfluidic devices is generally only one-dimensional using sheath flow. As a result, the equilibrium distribution of cells spreads beyond the focal plane of commonly used Gaussian laser excitation beams, resulting in a large number of blurred images that hinder subsequent cell sorting based on cell image features. To address this issue, we present a Bessel–Gaussian beam image-guided cell sorter with an ultra-long depth of focus, enabling focused images of >85% of passing cells. This system features label-free sorting capabilities based on features extracted from the output temporal waveform of a photomultiplier tube (PMT) detector. For the sorting of polystyrene beads, SKNO1 leukemia cells, and Scenedesmus green algae, our results indicate a sorting purity of 97%, 97%, and 98%, respectively, showing that the temporal waveforms from the PMT outputs have strong correlations with cell image features. These correlations are also confirmed by off-line reconstructed cell images from a temporal–spatial transformation algorithm tailored to the scanning Bessel–Gaussian beam.

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