Classification of platelet aggregates by intelligent imaging flow cytometry (Conference Presentation)

Yuqi Zhou; Atsushi Yasumoto; Cheng Lei; Chun-Jung Huang; Hirofumi Kobayashi; Yunzhao Wu; Sheng Yan; Chia-Wei Sun; Yutaka Yatomi; Keisuke Goda

doi:10.1117/12.2544194

10 March 2020 Classification of platelet aggregates by intelligent imaging flow cytometry (Conference Presentation)

Yuqi Zhou, Atsushi Yasumoto, Cheng Lei, Chun-Jung Huang, Hirofumi Kobayashi, Yunzhao Wu, Sheng Yan, Chia-Wei Sun, Yutaka Yatomi, Keisuke Goda

Author Affiliations +

Proceedings Volume 11250, High-Speed Biomedical Imaging and Spectroscopy V; 112500W (2020) https://doi.org/10.1117/12.2544194
Event: SPIE BiOS, 2020, San Francisco, California, United States

Abstract

Platelets participate in both physiological hemostasis and pathological thrombosis by forming aggregates activated by various agonists. However, it has been considered impossible to identify the stimuli and classify the aggregates. Here we present an intelligent method for classifying platelet aggregates by agonist type based on the combination of high-throughput imaging flow cytometry and a convolutional neural network. It morphologically identifies the contributions of different agonists to platelet aggregation with high accuracy. The method is a powerful tool for studying the underlying mechanism of platelet aggregation and is expected to develop a new class of clinical diagnostics and therapeutics.

Conference Presentation

Citation Download Citation

Yuqi Zhou, Atsushi Yasumoto, Cheng Lei, Chun-Jung Huang, Hirofumi Kobayashi, Yunzhao Wu, Sheng Yan, Chia-Wei Sun, Yutaka Yatomi, and Keisuke Goda "Classification of platelet aggregates by intelligent imaging flow cytometry (Conference Presentation)", Proc. SPIE 11250, High-Speed Biomedical Imaging and Spectroscopy V, 112500W (10 March 2020); https://doi.org/10.1117/12.2544194

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