Automated collective motion analysis validates human keratinocyte stem cell cultures.

ABSTRACT: Identification and quality assurance of stem cells cultured in heterogeneous cell populations are indispensable for successful stem cell therapy. Here we present an image-processing pipeline for automated identification and quality assessment of human keratinocyte stem cells. When cultivated under appropriate conditions, human epidermal keratinocyte stem cells give rise to colonies and exhibit higher locomotive capacity as well as significant proliferative potential. Image processing and kernel density estimation were used to automatically extract the area of keratinocyte colonies from phase-contrast images of cultures containing feeder cells. The DeepFlow algorithm was then used to calculate locomotion speed of the colony area by analyzing serial images. This image-processing pipeline suc

SUBMITTER: Kinoshita K 

PROVIDER: S-EPMC6904747 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature