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An automatic unsupervised classification of MR images in Alzheimer's disease
2010
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Image-analysis methods play an important role in helping detect brain changes in and diagnosis of Alzheimer's Disease (AD). In this paper, we propose an automatic unsupervised classification approach to distinguish brain magnetic resonance (MR) images of AD patients from those of elderly normal controls. The symmetric log-domain diffeomorphic demons algorithm, with the properties of symmetry and invertibility, is used to compute the pair-wise registration, whose deformation field is then used
doi:10.1109/cvpr.2010.5540031
dblp:conf/cvpr/LongW10
fatcat:6kphx7nuhve67andshzekf2xda