Application of multidimensional scaling to quantify shape in Alzheimer's disease and its correlation with Mini Mental State Examination: A feasibility study

Hyunjin Park, Jongbum Seo

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Today, high-resolution MRI scans are able to reveal even the fine details of brain structure. Several methods have been developed to quantify shape differences specific to scans of diseased brains. We have developed a novel method for quantifying shape information based on multidimensional scaling (MDS), a well-known statistical tool. Multidimensional scaling uses distance measures computed from pair-wise image registration of the training set. Image registration establishes spatial correspondence between scans in order to compare them in the same spatial framework. Our novel method has several advantages, including robustness to errors in registrations. Applying our method to 44 brain MRIs showed clear separation between normal and Alzheimer scans. Using our method as basis for classification between normal and Alzheimer scans yielded better performance results compared with using the volume of hippocampus as basis for classification. We also devised a simple measure derived from the MDS approach that was shown to correlate with the Mini Mental State Examination (MMSE), a well-known cognitive test for Alzheimer's disease.

Original languageEnglish
Pages (from-to)380-385
Number of pages6
JournalJournal of Neuroscience Methods
Volume194
Issue number2
DOIs
Publication statusPublished - 2011 Jan 15

Bibliographical note

Funding Information:
This study was supported by 1) Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology (grant 20100023233), 2) Business for Cooperative R&D between Industry, Academy, and Research Institute funded Korea Small and Medium Business Administration in 2010 (grant 0850110), and 3) Ministry of Knowledge Economy of Korea (grant 10030091).

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

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