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Author

C. Pennisi

2 papers indexed here

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Aug 2026

Automated Deep Learning Protocol for Quantifying Cell Viability in Live/Dead Fluorescence Microscopy.

A step-by-step protocol for automated cell viability quantification from two-channel live/dead fluorescence images using a deep learning pipeline built on a U-Net architecture with a ResNet-50 encoder pretrained on ImageNet, providing a reproducible framework adaptable to diverse cell types and imaging platforms.

Álvaro Díaz Vera, Khan Sharun, S. A. Banu et al. · 0 citations

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