Combining DTI and MRI for the automated detection of Alzheimer's disease using a large European multicenter dataset

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7509 LNCS, Issue , 2012, Pages 18-28

  Dyrba, Martin ^a,n   Ewers, Michael ^b,c   Wegrzyn, Martin ^a   Kilimann, Ingo ^a   Plant, Claudia ^d   Oswald, Annahita ^e   Meindl, Thomas ^f   Pievani, Michela ^g   Bokde, Arun L W ^h,i   Fellgiebel, Andreas ^j   Filippi, Massimo ^k   Hampel, Harald ^l   Klöppel, Stefan ^m   Hauenstein, Karlheinz ⁿ   Kirste, Thomas ⁿ   Teipel, Stefan J ^a,n  

^a GERMAN CENTER FOR NEURODEGENERATIVE DISEASES DZNE   (Germany)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c VETERANS AFFAIRS MEDICAL CENTER   (United States)

^d FLORIDA STATE UNIVERSITY   (United States)

^e UNIVERSITY OF MUNICH   (Germany)

^f LUDWIG MAXIMILIANS UNIVERSITY   (Germany)

^g IRCCS ISTITUTO CENTRO SAN GIOVANNI DI DIO FATEBENEFRATELLI   (Italy)

^h TRINITY COLLEGE DUBLIN   (Ireland)

ⁱ TRINITY COLLEGE DUBLIN   (Ireland)

^j UNIVERSITY MEDICAL CENTER MAINZ   (Germany)

^k VITA SALUTE SAN RAFFAELE UNIVERSITY   (Italy)

^l GOETHE UNIVERSITY   (Germany)

^m UNIVERSITY OF FREIBURG   (Germany)

ⁿ UNIVERSITY OF ROSTOCK   (Germany)

more..

Author keywords

Alzheimer's disease; combining classifiers; Diffusion Tensor Imaging; Magnetic Resonance Imaging; multicenter study; multimodal analysis; Support Vector Machine

Indexed keywords

ALZHEIMER'S DISEASE; AUTOMATED DETECTION; CLASSIFICATION PERFORMANCE; COGNITIVE IMPAIRMENT; COMBINING CLASSIFIERS; CROSS VALIDATION; DATA SETS; DETECTION RATES; FDG-PET; FRACTIONAL ANISOTROPY; FUNCTIONAL MRI; GREY MATTERS; IN-VIVO; MACHINE LEARNING TECHNIQUES; MEAN DIFFUSIVITY; MULTI-MODAL; MULTICENTER STUDY; MULTIMODAL ANALYSIS; MULTIMODAL DETECTION; NEUROIMAGING TECHNIQUES; NEURONAL FIBERS; RESEARCH QUESTIONS; STRUCTURAL NETWORKS; SVM CLASSIFICATION; WHITE MATTER;

DIFFUSION TENSOR IMAGING; IMAGE ANALYSIS; MAGNETIC RESONANCE IMAGING; SUPPORT VECTOR MACHINES;

TENSORS;

EID: 84868254722     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33530-3_2     Document Type: Conference Paper

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