Disease classification with hippocampal shape invariants

Boris Gutman, Yalin Wang, Jonathan Morra, Arthur W. Toga, Paul M. Thompson

Research output: Contribution to journalArticle

44 Scopus citations

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 languageEnglish (US)
Pages (from-to)572-578
Number of pages7
JournalHippocampus
Volume19
Issue number6
DOIs
StatePublished - Jun 1 2009
Externally publishedYes

Keywords

  • Alzheimer disease
  • Global shape description
  • Spherical harmonics
  • Spherical parameterization
  • Support vector machines

ASJC Scopus subject areas

  • Cognitive Neuroscience

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    Gutman, B., Wang, Y., Morra, J., Toga, A. W., & Thompson, P. M. (2009). Disease classification with hippocampal shape invariants. Hippocampus, 19(6), 572-578. https://doi.org/10.1002/hipo.20627