Label‐Free Imaging Flow Cytometry for Cell Classification Based on Multiple Interferometric Projections Using Deep Learning

Label‐Free Imaging Flow Cytometry for Cell Classification Based on Multiple Interferometric Projections Using Deep Learning

A new label‐free imaging flow cytometry method for noninvasive and automated biological cell classification is presented. Each cell is rolled during flow, and its off‐axis holograms from multiple viewpoints are acquired. Using the reconstructed quantitative phase profiles of the cell projections, hi...

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Bibliographic Details
Main Authors: Anat Cohen, Matan Dudaie, Itay Barnea, Francesca Borrelli, Jaromír Běhal, Lisa Miccio, Pasquale Memmolo, Vittorio Bianco, Pietro Ferraro, Natan T. Shaked
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:Advanced Intelligent Systems
Subjects:
cell classifications
convolutional neural networks
flow cytometry
interferometric phase microscopy
label-free imaging
Online Access:https://doi.org/10.1002/aisy.202300433

Internet

https://doi.org/10.1002/aisy.202300433

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