Alzheimer Disease detection on structural MRI

Olfa Ben Ahmed (1) , Jenny Benois-Pineau (2) , Michèle Allard (3) , Chokri Ben Amar (4) , Gwenaelle Catheline (3)

1 Image et Son
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique
3 INCIA - Institut de Neurosciences cognitives et intégratives d'Aquitaine
4 CEM Lab - ENIS - Département de Génie Électrique de Sfax [ENIS]

Alzheimer disease (AD) is the most common form of dementia. Structural (MRI) measurements allow detecting and following the evolution of brain atrophy which is a marker of the disease process. Recently, several pattern recognition methods have been proposed to automatically discriminate between patients with and without Alzheimer disease . Support Vector Machines help to identify patterns in data that differentiate between several classes. Hippocampus is the principal region involved in AD. In this work, we use visual description of the hippocampus ROI to detect Alzheimer disease from structural MR images.

Mots clés: BOVW; local features; ROI

Domaines: Multimédia [cs.MM]

Olfa Ben Ahmed, Jenny Benois-Pineau, Michèle Allard, Chokri Ben Amar, Gwenaelle Catheline. Alzheimer Disease detection on structural MRI. ESMRMB 2013 Congress, Oct 2013, Toulouse, France. ESMRMB, 1p, 2013. ⟨hal-00853850⟩