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S. Alizada

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Open access Aug 2026

Temporal dynamics improves machine learning-based prediction of cell state from quantitative phase imaging

Cell morphology reflects cell health and can distinguish cell-cycle stage, growth arrest, and distinct pathways of cell death. Live, label-free quantitative phase imaging (QPI) captures these features non-invasively and with high temporal resolution, yet many image-based classifiers rely on single frames and cannot sep...

S. Alizada, Kayla Marks, R. Zitnay et al. · 0 citations

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