Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/105049
Title: | A contact-imaging based microfluidic cytometer with machine-learning for single-frame super-resolution processing | Authors: | Huang, Xiwei Guo, Jinhong Wang, Xiaolong Yan, Mei Kang, Yuejun Yu, Hao |
Keywords: | DRNTU::Engineering::Chemical engineering::Biochemical engineering | Issue Date: | 2014 | Source: | Huang, X., Guo, J., Wang, X., Yan, M., Kang, Y., & Yu, H. (2014). A Contact-Imaging Based Microfluidic Cytometer with Machine-Learning for Single-Frame Super-Resolution Processing. PLoS ONE, 9(8), e104539-. | Series/Report no.: | PLoS one | Abstract: | Lensless microfluidic imaging with super-resolution processing has become a promising solution to miniaturize the conventional flow cytometer for point-of-care applications. The previous multi-frame super-resolution processing system can improve resolution but has limited cell flow rate and hence low throughput when capturing multiple subpixel-shifted cell images. This paper introduces a single-frame super-resolution processing with on-line machine-learning for contact images of cells. A corresponding contact-imaging based microfluidic cytometer prototype is demonstrated for cell recognition and counting. Compared with commercial flow cytometer, less than 8% error is observed for absolute number of microbeads; and 0.10 coefficient of variation is observed for cell-ratio of mixed RBC and HepG2 cells in solution. | URI: | https://hdl.handle.net/10356/105049 http://hdl.handle.net/10220/20408 |
ISSN: | 1932-6203 | DOI: | 10.1371/journal.pone.0104539 | Schools: | School of Chemical and Biomedical Engineering School of Electrical and Electronic Engineering |
Rights: | © 2014 Huang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles SCBE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
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journal.pone.0104539.pdf | 1.53 MB | Adobe PDF | View/Open |
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