Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI.

Dementia is a growing concern due to the aging process of the western societies. Non-invasive detection is therefore a high priority research endeavor. In this paper we report results of classification systems applied to the feature vectors obtained by a feature extraction method computed on structural magnetic resonance imaging (sMRI) volumes for the detection of two neurological disorders with cognitive impairment: myotonic dystrophy of type 1 (MD1) and Alzheimer disease (AD).