Patch-Based Morphometry: Application to Alzheimer's Disease

Pierrick Coupé (1, 2) , José V. Manjón (3) , Vladimir Fonov (1) , Simon F. Eskildsen (1, 4) , Louis D. Collins (1)

1 MNI - McConnell Brain Imaging Centre
2 LaBRI - Laboratoire Bordelais de Recherche en Informatique
3 ITACA
4 AAU - Aalborg University [Denmark]

While widely used to detect morphological differences between groups, Voxel-Based Morphometry (VBM) [1] is based on the assumption of one-to-one anatomical mapping between subjects and Gaussian distributions of focal tissue densities during statistical testing. To make data fit this model, tissue densities are blurred with large kernels at the expense of focal accuracy. To these issues, we propose a new Patch-Based Morphometry (PBM) method derived from our recently proposed innovative method to detect fine anatomical changes in MRI called Scoring by Nonlocal Image Patch Estimator [2]. SNIPE takes advantage of non-local analysis to handle the one-to-many mapping between brain anatomies. In this study, we extend SNIPE to the whole brain before comparing populations with PBM scores.

Domaines: Imagerie médicale; Traitement des images [eess.IV]; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]; Ingénierie biomédicale

Pierrick Coupé, José V. Manjón, Vladimir Fonov, Simon F. Eskildsen, Louis D. Collins. Patch-Based Morphometry: Application to Alzheimer's Disease. Alzheimer's Association International Conference, Jun 2012, Vancouver, Canada. epub ahead of print. ⟨hal-00684705⟩