Jing, Ning, Wang, Chao (2020) High Throughput Morphology-Based Cell Screening by Reservoir Computing. In: 2020 IEEE Photonics Conference (IPC). (doi:10.1109/IPC47351.2020.9252529) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:92173)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Contact us about this publication | |
| Official URL: https://doi.org/10.1109/IPC47351.2020.9252529 |
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Abstract
A new low-cost and data-efficient method for high-throughput microfluidic single-cell screening is proposed and demonstrated. Only one low-speed single-pixel photodetector is needed. Morphology-based object classification is achieved using reservoir computing. Our experiment shows that the frames involving the target cell can be recognized distinctly.
| Item Type: | Conference or workshop item (Paper) |
|---|---|
| DOI/Identification number: | 10.1109/IPC47351.2020.9252529 |
| Institutional Unit: | Schools > School of Engineering, Mathematics and Physics > Engineering |
| Former Institutional Unit: |
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
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| Depositing User: | Chao Wang |
| Date Deposited: | 06 Dec 2021 10:37 UTC |
| Last Modified: | 20 May 2025 10:46 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/92173 (The current URI for this page, for reference purposes) |
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