Longitudinal deformation models, spatial regularizations and learning strategies to quantify Alzheimer's disease progression

NeuroImage: Clinical

Volumn 4, Issue , 2014, Pages 718-729

  Fiot, Jean Baptiste ^a,b   Raguet, Hugo ^b   Risser, Laurent ^d   Cohen, Laurent D ^b   Fripp, Jurgen ^c   Vialard, François Xavier ^b  

^a IBM RESEARCH   (Ireland)

^b UNIVERSITÉ PARIS DAUPHINE   (France)

^c ROYAL BRISBANE AND WOMEN'S HOSPITAL   (Australia)

^d INSTITUT DE MATHÉMATIQUES DE TOULOUSE   (France)

Author keywords

Alzheimer's disease; Brain imaging; Coefficient map; Deformation model; Disease progression; Karcher mean; LDDMM; Logistic regression; Spatial regularization; Transport

Indexed keywords

ALZHEIMER DISEASE; ARTICLE; COMPARATIVE STUDY; DISEASE COURSE; FOLLOW UP; HIPPOCAMPUS; HUMAN; LOGISTIC REGRESSION ANALYSIS; LONGITUDINAL STUDY; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; BIOLOGICAL MODEL; FACTUAL DATABASE; IMAGE PROCESSING; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PATHOPHYSIOLOGY; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

ALZHEIMER DISEASE; DATABASES, FACTUAL; DISEASE PROGRESSION; HIPPOCAMPUS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LOGISTIC MODELS; MAGNETIC RESONANCE IMAGING; MILD COGNITIVE IMPAIRMENT; MODELS, NEUROLOGICAL;

EID: 84899674515     PISSN: None     EISSN: 22131582     Source Type: Journal    
DOI: 10.1016/j.nicl.2014.02.002     Document Type: Article

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