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We propose a new label-free method for noninvasive and automated cell processing for classification of WBCs. This is done by acquiring off-axis holograms of each cell during flow and achieving its optical path delay (OPD) profile. Based on this map, we extract highly discriminative features used to detect, classify, and differentiate between distinctive cells using a deep convolutional neural network. This label-free method might bring to new analysis tools for blood test processing.
Anat Cohen,Matan Dudaie,Itay Barnea, andNatan T. Shaked
"Label-free white blood cell classification during flow combining holographic imaging with deep learning", Proc. SPIE PC12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, PC126220L (12 August 2023); https://doi.org/10.1117/12.2670572
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Anat Cohen, Matan Dudaie, Itay Barnea, Natan T. Shaked, "Label-free white blood cell classification during flow combining holographic imaging with deep learning," Proc. SPIE PC12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, PC126220L (12 August 2023); https://doi.org/10.1117/12.2670572