Classification of human white blood cells using machine learning for stain-free imaging flow cytometry
Maxim Lippeveld, Carly Knill, Emma Ladlow, Andrew Fuller, Louise Jane Michaelis, Yvan Saeys, Andrew J. Filby, Daniel Peralta
This study compares classical machine learning and deep learning for classifying white blood cells using stain-free imaging flow cytometry, achieving balanced accuracies of 0.776 and 0.697 for white blood cells and 0.866 and 0.867 for eosinophils.
Cytometry Part A · Nov 5, 2019Peer-reviewedBioinformatics