Morphometric analysis of hippocampal shape in mild cognitive impairment: An imaging genetics study

Li Shen, Andrew J. Saykin, Moo K. Chung, Heng Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

A computational framework is presented for surface based morphometry to localize shape changes between groups of 3D objects. It employs the spherical harmonic (SPHARM) method for surface modeling and random field theory (RFT) for statistical inference. Several new components are introduced to overcome previous limitations: (1) a general linear model is used to facilitate controlling for covariates; (2) a new SPHARM registration method SHREC is proposed to better align SPHARM models; and (3) an estimated smoothness is used in RFT-based analysis to obtain more accurate results. This framework is applied in a mild cognitive impairment (MCI) study to examine hippocampal shape changes related to diagnostic and genetic conditions. Several interesting findings from our analyses suggest combining imaging phenotypes and genetic profiles has the potential to elucidate biological pathways for better understanding MCI and Alzheimer's disease.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Pages211-217
Number of pages7
DOIs
StatePublished - Dec 1 2007
Event7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE - Boston, MA, United States
Duration: Jan 14 2007Jan 17 2007

Publication series

NameProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

Other

Other7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
CountryUnited States
CityBoston, MA
Period1/14/071/17/07

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Bioengineering

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