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

Kimerly A. Powell; Laura R. Bohrer; Nicholas E. Stone; Bradley Hittle; Kristin R. Anfinson; Viviane Luangphakdy; George Muschler; Robert F. Mullins; Edwin M. Stone; Budd A. Tucker

doi:10.1016/j.slast.2023.07.004

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

Journal article

Open access

Peer reviewed

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

Kimerly A. Powell, Laura R. Bohrer, Nicholas E. Stone, Bradley Hittle, Kristin R. Anfinson, Viviane Luangphakdy, George Muschler, Robert F. Mullins, Edwin M. Stone and Budd A. Tucker

SLAS technology, Vol.28(6), pp.416-422

12/2023

DOI: 10.1016/j.slast.2023.07.004

PMCID: PMC10775697

PMID: 37454765

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https://doi.org/10.1016/j.slast.2023.07.004View

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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 CellXTM 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 CellXTM 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.

Automated image analysis cell cultures

Deep Learning

Human induced pluripotent stem cell (hiPSC) processing

Stem Cell Manufacturing

Details

Title: Subtitle: Automated human induced pluripotent stem cell colony segmentation for use in cell culture automation applications
Creators: Kimerly A. Powell - The Ohio State University
Laura R. Bohrer - University of Iowa
Nicholas E. Stone - University of Iowa
Bradley Hittle - The Ohio State University
Kristin R. Anfinson - University of Iowa
Viviane Luangphakdy - Cleveland Clinic Lerner College of Medicine
George Muschler - Cleveland Clinic
Robert F. Mullins - University of Iowa
Edwin M. Stone - University of Iowa
Budd A. Tucker - University of Iowa
Resource Type: Journal article
Publication Details: SLAS technology, Vol.28(6), pp.416-422
DOI: 10.1016/j.slast.2023.07.004
PMID: 37454765
PMCID: PMC10775697
NLM abbreviation: SLAS Technol
ISSN: 2472-6303
eISSN: 2472-6311
Publisher: Elsevier Inc
Language: English
Electronic publication date: 07/14/2023
Date published: 12/2023
Academic Unit: The University of Iowa Institute for Vision Research; Iowa Neuroscience Institute; John and Marcia Carver Nonprofit Genetic Testing Laboratory; Ophthalmology and Visual Sciences
Record Identifier: 9984445527402771

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