Colony morphology (CM) is an important criterion to evaluate health of Pluripotent Stem Cells (PSCs) in culture or to select induced-PSC colonies after reprogramming. However, manual evaluation of CM is time-consuming, not quantitative and poorly reproducible. We designed an unbiased method to evaluate CM of non-labeled PSCs using microplate images acquired from a flatbed scanner. The high-throughput automated analysis is based on image processing and algorithms for segmentation, count and multi-parametric classification of colonies.

Imaging for High-Throughput Screening of Pluripotent Stem Cells

L Casalino;M R Guarracino;L Maddalena
2018

Abstract

Colony morphology (CM) is an important criterion to evaluate health of Pluripotent Stem Cells (PSCs) in culture or to select induced-PSC colonies after reprogramming. However, manual evaluation of CM is time-consuming, not quantitative and poorly reproducible. We designed an unbiased method to evaluate CM of non-labeled PSCs using microplate images acquired from a flatbed scanner. The high-throughput automated analysis is based on image processing and algorithms for segmentation, count and multi-parametric classification of colonies.
2018
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
image segmentation
machine learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/371185
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