Using Support Vector Machines with Multiple Indices of Diffusion for Automated Classification of Mild Cognitive Impairment
Open Access
- 23 February 2012
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLOS ONE
- Vol. 7 (2), e32441
- https://doi.org/10.1371/journal.pone.0032441
Abstract
Few studies have looked at the potential of using diffusion tensor imaging (DTI) in conjunction with machine learning algorithms in order to automate the classification of healthy older subjects and subjects with mild cognitive impairment (MCI). Here we apply DTI to 40 healthy older subjects and 33 MCI subjects in order to derive values for multiple indices of diffusion within the white matter voxels of each subject. DTI measures were then used together with support vector machines (SVMs) to classify control and MCI subjects. Greater than 90% sensitivity and specificity was achieved using this method, demonstrating the potential of a joint DTI and SVM pipeline for fast, objective classification of healthy older and MCI subjects. Such tools may be useful for large scale drug trials in Alzheimer's disease where the early identification of subjects with MCI is critical.Keywords
This publication has 50 references indexed in Scilit:
- Enriched white matter connectivity networks for accurate identification of MCI patientsNeuroImage, 2011
- Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's diseaseNeuroImage, 2010
- Automated MRI measures identify individuals with mild cognitive impairment and Alzheimer's diseaseBrain, 2009
- Tensor-based morphometry as a neuroimaging biomarker for Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjectsNeuroImage, 2008
- Structural and functional biomarkers of prodromal Alzheimer's disease: A high-dimensional pattern classification studyNeuroImage, 2008
- Automatic classification of MR scans in Alzheimer's diseaseBrain, 2008
- Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive declineNeuroImage, 2007
- Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer diseaseNeurology, 2007
- Detection of prodromal Alzheimer's disease via pattern classification of magnetic resonance imagingNeurobiology of Aging, 2006
- Clinical diagnosis of Alzheimer's diseaseNeurology, 1984