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arXiv:1712.07639cs.CV

Image Segmentation to Distinguish Between Overlapping Human Chromosomes

R. Lily Hu, Jeremy Karnowski, Ross Fadely, Jean-Patrick Pommier

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Abstract

In medicine, visualizing chromosomes is important for medical diagnostics, drug development, and biomedical research. Unfortunately, chromosomes often overlap and it is necessary to identify and distinguish between the overlapping chromosomes. A segmentation solution that is fast and automated will enable scaling of cost effective medicine and biomedical research. We apply neural network-based image segmentation to the problem of distinguishing between partially overlapping DNA chromosomes. A convolutional neural network is customized for this problem. The results achieved intersection over union (IOU) scores of 94.7% for the overlapping region and 88-94% on the non-overlapping chromosome regions.

arXiv comments
Presented at NIPS 2017 Machine Learning for Health
Journal reference
DOI
Subjects
cs.CVComputer Vision and Pattern Recognition cs.LGMachine Learning q-bio.QMQuantitative Methods stat.MLMachine Learning (Statistics)

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