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Article

CenSegNet: a generalist high-throughput deep learning framework for centrosome phenotyping at spatial and single-cell resolution in heterogeneous tissues.

Nature communications - 15 Jul 2026

Cheng Jiaoqi, Fan Keqiang, Bailey Miles, Du Xin, Jena Rajesh, Savva Constantinos, Reed Ewan, Gou Mengyang, Zuo Peixin, Cutress Ramsey, Beers Stephen, Cai Xiaohao, Elias Salah

Abstract excerpt

Centrosome abnormalities (CA) are a hallmark of epithelial cancers, yet their spatial complexity and phenotypic heterogeneity remain poorly understood due to limitations in conventional image analysis. Here we present CenSegNet (Centrosome Segmentation Network), a modular deep learning framework for high-throughput segmentation of centrosomes and epithelial architecture, enabling accurate and generalisable...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 42457714
DOI: 10.1038/s41467-026-75393-y
PMCID: PMC13490574

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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