Pavel Falkovskiy1,2,3, Bénédicte Maréchal1,2,3, Tobias Kober1,2,3, Philippe Maeder1, Reto Meuli1, Jean-Philippe Thiran3, and Alexis Roche1,2,3
1Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland, 2Advanced Clinical Imaging Technology (HC CMEA SUI DI BM PI), Siemens Healthcare AG, Lausanne, Switzerland, 3LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
We investigate the potentially confounding effect of using different image acquisition systems (field strength, manufacturers) on automated Alzheimer's disease detection using standardized Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Disease classifiers based on brain volumetric markers computed by FreeSurfer and the MorphoBox prototype were evaluated with and without correcting for variations in acquisition systems. While the correction overall had limited impact on Alzheimer's disease detection, it enabled significant error reduction for the classification of mildly cognitively impaired patients versus both healthy controls and Alzheimer's patients.
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