Event-Preserving Neural Network Denoising for Impedance Flow Cytometry
Leilei Shi, Charlie Jindrich · 2026
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Description
Leilei Shi and Charlie Jindrich present a 2026 method to clean noisy signals from a chip that tests single cells. The chip senses each cell by a brief shift in electric flow as it passes small probes. Noise, drift, and false blips can hide true cells or warp the traits drawn from each blip.
Their neural network learns to cut noise while keeping true cell events whole. Training leans on real events, and the loss gives extra weight to the spans that hold them. Clean output helps labs count and sort cells with more trust, at high speed and with no dyes or tags.
Catalog record
| CREATOR | Leilei Shi, Charlie Jindrich |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |