Detection of cells by flow cytometry: Counting, imaging, and cell classification

Polarimetry is a powerful optical tool in the biomedical field, providing more comprehensive information on the sub-wavelength micro-physical structure of a sample than traditional light intensity measurement techniques. This review summarizes the concepts and techniques of polarization and its biomedical applications. Specifically, we first briefly describe the basic principles of polarized light and the Mueller matrix (MM) decomposition method, followed by some research progress of polarimetric measurement techniques in recent years. Finally, we introduce some studies on biological tissues and cells, and then illustrate the application value of polarization optical method.

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Label-free in-vivo classification and tracking of red blood cells and platelets using Dynamic-YOLOv4 network

Guan,

He,

Zhang

et al. 2024

J. Innov. Opt. Health Sci.

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In-vivo flow cytometry is a noninvasive real-time diagnostic technique that facilitates continuous monitoring of cells without perturbing their natural biological environment, which renders it a valuable tool for both scientific research and clinical applications. However, the conventional approach for improving classification accuracy often involves labeling cells with fluorescence, which can lead to potential phototoxicity. This study proposes a label-free in-vivo flow cytometry technique, called dynamic YOLOv4 (D-YOLOv4), which improves classification accuracy by integrating absorption intensity fluctuation modulation (AIFM) into YOLOv4 to demodulate the temporal features of moving red blood cells (RBCs) and platelets. Using zebrafish as an experimental model, the D-YOLOv4 method achieved average precisions (APs) of 0.90 for RBCs and 0.64 for thrombocytes (similar to platelets in mammals), resulting in an overall AP of 0.77. These scores notably surpass those attained by alternative network models, thereby demonstrating that the combination of physical models with neural networks provides an innovative approach toward developing label-free in-vivo flow cytometry, which holds promise for diverse in-vivo cell classification applications.

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Detection of cells by flow cytometry: Counting, imaging, and cell classification

Cited by 4 publications

References 69 publications

Introduction to special issue on single cell analysis (Part II)

Introduction to special issue on single cell analysis (Part II)

Review of polarization-based technology for biomedical applications

Label-free in-vivo classification and tracking of red blood cells and platelets using Dynamic-YOLOv4 network

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