• DocumentCode
    1771585
  • Title

    Classification of amnestic mild cognitive impairment using fMRI

  • Author

    Mingwu Jin ; Curran, Tim ; Cordes, Dietmar

  • Author_Institution
    Phys., Univ. of Texas at Arlington, Arlington, TX, USA
  • fYear
    2014
  • fDate
    April 29 2014-May 2 2014
  • Firstpage
    29
  • Lastpage
    32
  • Abstract
    In this work, the feasibility of classifying amnestic mild cognitive impairment (aMCI), a prodromal stage of Alzheimer´s disease, was investigated using fMRI activation patterns in the medial temporal lobes (MTL). The activation volume or relative activation extent in each of fourteen subregions of the MTL, when subjects were performing memory tasks, served as features for radial basis function networks (RBFN). The prediction performance was assessed among all combinations of subregions in different memory paradigms and contrasts. A high prediction accuracy of 93.75% (p=2.44×10-4) was achieved by as few as two subregions with one contrast. This result demonstrates the possibility of using compact fMRI activation patterns to aid in the diagnosis of aMCI.
  • Keywords
    biomedical MRI; cognition; diseases; image classification; medical disorders; medical image processing; neurophysiology; radial basis function networks; Alzheimer disease; MTL; RBFN; aMCI classification; aMCI diagnosis; activation volume; amnestic mild cognitive impairment; fMRI activation patterns; medial temporal lobes; memory tasks; radial basis function networks; relative activation extent; Accuracy; Aging; Alzheimer´s disease; Hippocampus; Image resolution; Magnetic resonance imaging; Training; amnestic mild cognitive impairment; classification; fMRI activation pattern; medial temporal lobe; radial basis function network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/ISBI.2014.6867801
  • Filename
    6867801