What is it about?

We used machine learning to discriminate normal from abnormal chromosomes that result from radiation exposure

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Why is it important?

The number of abnormal chromosomes present can be used to determine how much radiation a person has received. Overradiated individuals need to be treated.


The method we developed is more accurate than any previously described. This paper was key to the development of our Automated Dicentric Chromosome Identifier and Dose Estimation product marketed by CytoGnomix.

Dr Peter K Rogan
Western University

Read the Original

This page is a summary of: Automated discrimination of dicentric and monocentric chromosomes by machine learning-based image processing, Microscopy Research and Technique, March 2016, Wiley, DOI: 10.1002/jemt.22642.
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