Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers

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Summary

This thesis is devoted to developing fully automated methods for quantification of small vessel disease imaging bio-markers, namely WMHs and lacunes, using machine learning/deep learning and computer vision techniques, using biologically inspired methods combined with deep neural networks.

Published
2018-01-01
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