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Abstract #4733

Volume-based vs. voxel-based brain morphometry in Alzheimer's disease prediction

Alexis Roche 1,2 , Daniel Schmitter 1,3 , Bndicte Marchal 1 , Delphine Ribes 1 , Ahmed Abdulkadir 4 , Meritxell Bach-Cuadra 2,5 , Alessandro Daducci 5 , Cristina Granziera 1,6 , Stefan Klppel 4 , Philippe Maeder 2 , Reto Meuli 2 , and Gunnar Krueger 1

1 Advanced Clinical Imaging Technology, Siemens Healthcare IM BM PI, Lausanne, Switzerland, 2 Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 3 Biomedical Imaging Group, EPFL, Lausanne, Switzerland, 4 Group of Pattern Recognition and Image Processing, University of Freiburg, Germany, 5 Signal Processing Laboratory 5, EPFL, Lausanne, Switzerland, 6 Service of Neurology, University Hospital (CHUV), Lausanne, Switzerland

This study compares different MR T1-based brain morphometry methods for automated classification of Alzheimer patients, mild cognitively impaired patients and elderly controls on a standardized analysis set of 818 scans from the ADNI NIH-funded project. The methods under investigation are standard voxel-based morphometry, as implemented by the SPM software, and volume-based morphometry as implemented in respectively different ways by FreeSurfer and Siemens prototype MorphoBox. Our results show that classification using volume-based morphometry is at least as accurate as voxel-based morphometry, therefore proving volume-based morphometry to be a valuable methodology to assist the diagnosis of Alzheimer's disease and mild cognitive impairment.

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