Deep learning-enabled imaging flow cytometry for high-speed Cryptosporidium and Giardia detection

Deep learning-enabled imaging flow cytometry for high-speed Cryptosporidium and Giardia detection

Imaging flow cytometry has become a popular technology for bioparticle image analysis because of its capability of capturing thousands of images per second. Nevertheless, the vast number of images generated by imaging flow cytometry imposes great challenges for data analysis especially when the spec...

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Bibliographic Details
Main Authors: Luo, Shaobo, Nguyen, Kim Truc, Nguyen, Binh Thi Thanh, Feng, Shilun, Shi, Yuzhi, Elsayed, Ahmed, Zhang, Yi, Zhou, Xiaohong, Wen, Bihan, Chierchia, Giovanni, Talbot, Hugues, Bourouina, Tarik, Jiang, Xudong, Liu, Ai Qun
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2022
Subjects:
Engineering::Electrical and electronic engineering
Cell Classification
Deep Learning
Online Access:https://hdl.handle.net/10356/155664

Internet

https://hdl.handle.net/10356/155664

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