Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison

Because of its non-destructive nature, label-free imaging is an important strategy for studying biological processes. However, routine microscopic techniques like phase contrast or DIC suffer from shadow-cast artifacts making automatic segmentation challenging. The aim of this study was to compare the segmentation efficacy of published steps of segmentation work-flow (image reconstruction, foreground segmentation, cell detection (seed-point extraction) and cell (instance) segmentation) on a dataset of the same cells from multiple contrast microscopic modalities.

Keywords

Microscopy, Cell segmentation, Image reconstruction, Methods comparison, Differential contrast image, Quantitative phase imaging, Laplacian of Gaussians

Citation

BMC BIOINFORMATICS. 2019, vol. 20, issue 1, p. 1-25.
https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2880-8

Document type

Peer-reviewed

Document version

Published version

Language of document

en

Document licence

Creative Commons Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/