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Hippocampus. 2009 Jun;19(6):572-8. doi: 10.1002/hipo.20627.

Disease classification with hippocampal shape invariants.

Author information

1
Laboratory of Neuro Imaging, Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, California, USA. bgutman@ucla.edu

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 classification 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.

PMID:
19437498
PMCID:
PMC3113700
DOI:
10.1002/hipo.20627
[Indexed for MEDLINE]
Free PMC Article

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