Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip
SCIE
SCOPUS
- Title
- Real-time Image Processing for Microscopy-based Label-free Imaging Flow Cytometry in a Microfluidic Chip
- Authors
- Heo, Young Jin; Lee, Donghyeon; Kang, Junsu; Lee, Keondo; Chung, Wan Kyun
- Date Issued
- 2017-09
- Publisher
- Nature Publishing Group
- Abstract
- Imaging flow cytometry (IFC) is an emerging technology that acquires single-cell images at high-throughput for analysis of a cell population. Rich information that comes from high sensitivity and spatial resolution of a single-cell microscopic image is beneficial for single-cell analysis in various biological applications. In this paper, we present a fast image-processing pipeline (R-MOD: Real-time Moving Object Detector) based on deep learning for high-throughput microscopy-based label-free IFC in a microfluidic chip. The R-MOD pipeline acquires all single-cell images of cells in flow, and identifies the acquired images as a real-time process with minimum hardware that consists of a microscope and a high-speed camera. Experiments show that R-MOD has the fast and reliable accuracy (500 fps and 93.3% mAP), and is expected to be used as a powerful tool for biomedical and clinical applications.
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/50994
- DOI
- 10.1038/s41598-017-11534-0
- ISSN
- 2045-2322
- Article Type
- Article
- Citation
- Scientific Reports, vol. 7, 2017-09
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