A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei

Pei-Hsun Wu, Denis Wirtz, Jude M. Phillip, Kyu-Sang Han, Wei-Chiang Chen

Published: 2021-01-10 DOI: 10.1038/s41596-020-00432-x

Quantification

Machine-learning

Cell morphology

Morphological heterogeneity

VAMPIRE algorithm

AI 解读

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Cell morphology encodes essential information on many underlying biological processes. It is commonly used by clinicians and researchers in the study, diagnosis, prognosis, and treatment of human diseases. Quantification of cell morphology has seen tremen
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ACKNOWLEDGMENTS
ACKNOWLEDGMENTS

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A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei

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