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
- Cited by
- 1
- References
- 200
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:215766538
References
- [The concept of cerebral lacunae from 1838 to the present].
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