Urish, KL and Deasy, BM and Huard, J
(2013)
Automated classification and visualization of fluorescent live cell microscopy images.
Journal of Microscopy, 249 (3).
206 - 214.
ISSN 0022-2720
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Abstract
Robotic, high-throughput microscopy is a powerful tool for small molecule screening and classifying cell phenotype, proteomic and genomic data. An important hurdle in the field is the automated classification and visualization of results collected from a data set of tens of thousands of images. We present a method that approaches these problems from the perspective of flow cytometry with supporting open-source code. Image analysis software was created that allowed high-throughput microscopy data to be analysed in a similar manner as flow cytometry. Each cell on an image is considered an object and a series of gates similar to flow cytometry is used to classify and quantify the properties of cells including size and level of fluorescent intensity. This method is released with open-source software and code that demonstrates the method's implementation. Accuracy of the software was determined by measuring the levels of apoptosis in a primary murine myoblast cell line after exposure to staurosporine and comparing these results to flow cytometry. © 2013 Royal Microscopical Society.
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