AI RESEARCH
Towards Label-Free Single-Cell Phenotyping Using Multi-Task Learning
arXiv CS.CV
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ArXi:2605.14717v1 Announce Type: new Label-free single-cell imaging offers a scalable, non-invasive alternative to fluorescence-based cytometry, yet inferring molecular phenotypes directly from bright-field morphology remains challenging. We present a unified Deep Learning (DL) framework that jointly performs White Blood Cell (WBC) classification and continuous protein-expression regression from label-free Differential Phase Contrast (DPC) images.