Automatic classification of SPECT images of Alzheimer's disease patients and control subjects

In this article we study the use of SPECT perfusion imaging for the diagnosis of Alzheimer's disease. We present a classifier based approach that does not need any explicit knowledge about the pathology. We directly use the voxel intensities as features. This approach is compared with three classical approaches: regions of interests, statistical parametric mapping and visual analysis which is the most commonly used method. We tested our method both on simulated and on real data. The realistic simulations give us total control about the ground truth. On real data, our method was more sensitive than the human experts, while having an acceptable specificity. We conclude that an automatic method can be a useful help for clinicians. © Springer-Verlag Berlin Heidelberg 2004.