Benoit Magnin

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We present and evaluate a new automated method based on support vector machine (SVM) classification of whole-brain anatomical magnetic resonance imaging to discriminate between patients with Alzheimer’s disease (AD) and elderly control subjects. We studied 16 patients with AD [mean age ± standard deviation (SD) = 74.1 ± 5.2 years, mini-mental score(More)
PURPOSE To prospectively evaluate the accuracy of automated hippocampal volumetry to help distinguish between patients with Alzheimer disease (AD), patients with mild cognitive impairment (MCI), and elderly controls, by using established criteria for patients with AD and MCI as the reference standard. MATERIALS AND METHODS The regional ethics committee(More)
In this paper, we propose a fully automated method to individually classify patients with Alzheimer’s disease (AD) and elderly control subjects based on anatomical magnetic resonance imaging (MRI). Our approach relies on the identification of gray matter (GM) atrophy patterns using whole-brain parcellation into anatomical regions and the extraction of GM(More)
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