End-to-end plaque counting and virus titration from laboratory plate images with deep learning
Plaque assays remain the gold standard readout of virus infectivity; however, plaque counting from plate images is labor-intensive and prone to inter-operator variability. We present an end-to-end, computer-aided workflow for cytopathic effect-based virus titration directly from laboratory plaque assay images. The proposed approach combines two models derived from the Segment Anything Model (SAM): a SAM2-based well-segmentation module that localizes assay wells across heterogeneous imaging conditions, and a SAM-based plaque-segmentation model that detects and enumerates plaques within each well. The method was evaluated on a mixed dataset comprising private plaque assay images of Mayaro v...
| Authors | Eugenia Moris, Alicia Costábile, Sebastián Rey et al. |
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| Primary category | cs.CV |
| Published | 15 May 2026 |
| Last updated at source | 15 May 2026 |
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