Early diagnosis of Alzheimer's disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images

Neurocomputing

Volumn 151, Issue P1, 2015, Pages 139-150

  Khedher, L ^a   Ramirez J ^a   Gorriz J M ^a   Brahim, A ^a   Segovia, F ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

ADNI database; Alzheimer disease; Computer aided diagnosis system; PCA; PLS; Support vector machine

Indexed keywords

BRAIN MAPPING; CLASSIFICATION (OF INFORMATION); COMPUTER AIDED DIAGNOSIS; DATABASE SYSTEMS; DIAGNOSIS; DISEASE CONTROL; EXTRACTION; FEATURE EXTRACTION; IMAGE SEGMENTATION; IMAGING TECHNIQUES; LEAST SQUARES APPROXIMATIONS; MAGNETIC RESONANCE IMAGING; NEURODEGENERATIVE DISEASES; NEUROIMAGING; RADIAL BASIS FUNCTION NETWORKS; SUPPORT VECTOR MACHINES; TISSUE;

ALZHEIMER DISEASE; COMPUTER AIDED DIAGNOSIS SYSTEMS; COMPUTER AIDED DIAGNOSIS(CAD); MILD COGNITIVE IMPAIRMENTS (MCI); PCA; PLS; RADIAL BASIS FUNCTION(RBF); SUPPORT VECTOR MACHINE CLASSIFIERS;

PRINCIPAL COMPONENT ANALYSIS;

AGED; ALZHEIMER DISEASE; ARTICLE; CLASSIFIER; COMPUTER ASSISTED DIAGNOSIS; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; DIFFERENTIAL DIAGNOSIS; EARLY DIAGNOSIS; FEMALE; GRAY MATTER; HUMAN; MAJOR CLINICAL STUDY; MALE; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; PARTIAL LEAST SQUARES REGRESSION; PRINCIPAL COMPONENT ANALYSIS; RADIAL BASED FUNCTION; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; TISSUE DISTRIBUTION; WHITE MATTER;

EID: 84922781392     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2014.09.072     Document Type: Article

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