Abstract
We present an Alzheimer's detection study based on a global shape description of hippocampal surface models. With global descriptors forming our bag of features, Support Vector Machine classi-fication of 49 Alzheimer(AD) and 63 elderly control subjects yielded 75.5% sensitivity and 87.3% specificity with 82.1% correct overall in a leave-one-out test. We show that our description contributes new information to simpler shape measures. Armed with a rigid shape registration tool, we also present a way to visualize variation in global shape description as a local displacement map, thus clarifying the descriptors' anatomical meaning.
Original language | English (US) |
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Pages (from-to) | 572-578 |
Number of pages | 7 |
Journal | Hippocampus |
Volume | 19 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2009 |
Externally published | Yes |
Keywords
- Alzheimer disease
- Global shape description
- Spherical harmonics
- Spherical parameterization
- Support vector machines
ASJC Scopus subject areas
- Cognitive Neuroscience