Issue 5, 2024

Classification of chemically modified red blood cells in microflow using machine learning video analysis

Abstract

We classify native and chemically modified red blood cells with an AI based video classifier. Using TensorFlow video analysis enables us to capture not only the morphology of the cell but also the trajectories of motion of individual red blood cells and their dynamics. We chemically modify cells in three different ways to model different pathological conditions and obtain classification accuracies for all three classification tasks of more than 90% between native and modified cells. Unlike standard cytometers that are based on immunophenotyping our microfluidic cytometer allows to rapidly categorize cells without any fluorescence labels simply by analysing the shape and flow of red blood cells.

Graphical abstract: Classification of chemically modified red blood cells in microflow using machine learning video analysis

Article information

Article type
Paper
Submitted
05 10月 2023
Accepted
25 11月 2023
First published
04 12月 2023
This article is Open Access
Creative Commons BY license

Soft Matter, 2024,20, 952-958

Classification of chemically modified red blood cells in microflow using machine learning video analysis

R. K. R. Baskaran, A. Link, B. Porr and T. Franke, Soft Matter, 2024, 20, 952 DOI: 10.1039/D3SM01337E

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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