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Automated human induced pluripotent stem cell colony segmentation for use in cell culture automation applications. | LitMetric

Automated human induced pluripotent stem cell colony segmentation for use in cell culture automation applications.

SLAS Technol

Institute for Vision Research, Carver College of Medicine, University of Iowa, Iowa City, IA, USA; Department of Ophthalmology and Visual Sciences, Carver College of Medicine, University of Iowa, Iowa City, IA, USA.

Published: December 2023

AI Article Synopsis

Article Abstract

Human induced pluripotent stem cells (hiPSCs) have demonstrated great promise for a variety of applications that include cell therapy and regenerative medicine. Production of clinical grade hiPSCs requires reproducible manufacturing methods with stringent quality-controls such as those provided by image-controlled robotic processing systems. In this paper we present an automated image analysis method for identifying and picking hiPSC colonies for clonal expansion using the CellX robotic cell processing system. This method couples a light weight deep learning segmentation approach based on the U-Net architecture to automatically segment the hiPSC colonies in full field of view (FOV) high resolution phase contrast images with a standardized approach for suggesting pick locations. The utility of this method is demonstrated using images and data obtained from the CellX system where clinical grade hiPSCs were reprogrammed, clonally expanded, and differentiated into retinal organoids for use in treatment of patients with inherited retinal degenerative blindness.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10775697PMC
http://dx.doi.org/10.1016/j.slast.2023.07.004DOI Listing

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