A new statistical image analysis approach and its application to Hippocampal morphometry

ADNI

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

1 Scopus citations

Abstract

In this work, we propose a novel and powerful image analysis framework for hippocampal morphometry in early mild cognitive impairment (EMCI), an early prodromal stage of Alzheimer’s disease (AD). We create a hippocampal surface atlas with subfield information, model each hippocampus using the SPHARM technique, and register it to the atlas to extract surface deformation signals. We propose a new alternative to standard random field theory (RFT) and permutation image analysis methods, Statistical Parametric Mapping (SPM) Distribution Analysis or SPM-DA, to perform statistical shape analysis and compare its performance with that of RFT methods on both simulated and real hippocampal surface data. The major strengths of our framework are twofold: (a) SPM-DA provides potentially more powerful algorithms than standard RFT methods for detecting weak signals, and (b) the framework embraces the important hippocampal subfield information for improved biological interpretation. We demonstrate the effectiveness of our method via an application to an AD cohort, where an SPM-DA method detects meaningful hippocampal shape differences in EMCI that are undetected by standard RFT methods.

Original languageEnglish (US)
Title of host publicationMedical Imaging and Augmented Reality - 7th International Conference, MIAR 2016, Proceedings
EditorsHongen Liao, Guoyan Zheng, Su-Lin Lee, Philippe Cattin, Pierre Jannin
PublisherSpringer Verlag
Pages302-310
Number of pages9
ISBN (Print)9783319437743
DOIs
StatePublished - Jan 1 2016
Event7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016 - Bern, Switzerland
Duration: Aug 24 2016Aug 26 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9805 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016
CountrySwitzerland
CityBern
Period8/24/168/26/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    ADNI (2016). A new statistical image analysis approach and its application to Hippocampal morphometry. In H. Liao, G. Zheng, S-L. Lee, P. Cattin, & P. Jannin (Eds.), Medical Imaging and Augmented Reality - 7th International Conference, MIAR 2016, Proceedings (pp. 302-310). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9805 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-43775-0_27