Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Deep Learning Object Detection

Publication type: Proceedings Article
Publication date: 2020-11-02
Institute of Electrical and Electronics Engineers (IEEE)
Abstract
The method based on convolutional neural networks usage is developed for evaluation of particle-cell interactions. The imaging flow cytometry was used for automatic mining of important cell-particle interaction information. The developed method expands capabilities of spot counting applications in existing imaging techniques and allows to quantify particle-cell and cell-cell interactions.
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Kotov I. A., Mochalova E. N., Kolychev E. L. Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Deep Learning Object Detection // Proceedings - International Conference Laser Optics 2020, ICLO 2020. 2020.
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Kotov I. A., Mochalova E. N., Kolychev E. L. Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Deep Learning Object Detection // Proceedings - International Conference Laser Optics 2020, ICLO 2020. 2020.
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TY - CPAPER
DO - 10.1109/ICLO48556.2020.9285899
UR - https://doi.org/10.1109/ICLO48556.2020.9285899
TI - Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Deep Learning Object Detection
T2 - Proceedings - International Conference Laser Optics 2020, ICLO 2020
AU - Kotov, I A
AU - Mochalova, Elizaveta N
AU - Kolychev, E L
PY - 2020
DA - 2020/11/02
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -
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@inproceedings{2020_Kotov,
author = {I A Kotov and Elizaveta N Mochalova and E L Kolychev},
title = {Precise Quantitative Analysis of Cell Targeting by Particle-Based Agents Using Imaging Flow Cytometry and Deep Learning Object Detection},
year = {2020},
month = {nov},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)}
}