Code-multiplexed multi-frequency impedance cytometry with a unified deep-unfolding network
This article introduces a unified deep-unfolding network designed to analyze complex code-multiplexed, multi-frequency impedance flow cytometry (IFC) data, a label-free single-cell measurement technique. The network improves accuracy by resolving signal overlaps and mitigating nonlinearities, enabling precise multi-frequency impedance profiling for applications like quantifying basophil activation.
Why it matters
This advancement in signal processing for IFC allows for more accurate and parallelized single-cell analysis, providing deeper insights into biophysical properties without traditional labels, which is crucial for medical diagnostics and biological research.
Microsystems & Nanoengineering volume 12 , Article number: 325 ( 2026 ) Cite this article
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