multi-method analysis of mri images in early diagnostics of alzheimers disease核磁共振图像的方法分析阿尔茨海默病的早期诊断.pdfVIP

Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer’s Disease 1. 2. 3 2,4 1 Robin Wolz , Valtteri Julkunen , Juha Koikkalainen , Eini Niskanen , Dong Ping Zhang , Daniel 1 2,5 ¨ ¨ 3 Rueckert , Hilkka Soininen , Jyrki Lotjonen *, the Alzheimer’s Disease Neuroimaging Initiative 1 Biomedical Image Analysis Group, Department of Computing, Imperial College London, London, United Kingdom, 2 Department of Neurology, Kuopio University Hospital, Kuopio, Finland, 3 Knowledge Intensive Services, VTT Technical Research Centre of Finland, Tampere, Finland, 4 Department of Applied Physics, University of Eastern Finland, Kuopio, Finland, 5 Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland Abstract The role of structural brain magnetic resonance imaging (MRI) is becoming more and more emphasized in the early diagnostics of Alzheimer’s disease (AD). This study aimed to assess the improvement in classification accuracy that can be achieved by combining features from different structural MRI analysis techniques. Automatically estimated MR features used are hippocampal volume, tensor-based morphometry, cortical thickness and a novel technique based on manifold learning. Baseline MRIs acquired from all 834 subjects (231 healthy controls (HC), 238 stable mild cognitive impairment (S- MCI), 167 MCI to AD progressors (P-MCI), 198 AD) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database were used for evaluation. We compared the classificat