Detecting anatomical landmarks for fast Alzheimer's disease diagnosis

IEEE Transactions on Medical Imaging

Volumn 35, Issue 12, 2016, Pages 2524-2533

  Zhang, Jun ^a   Gao, Yue ^a   Gao, Yaozong ^a,b   Munsell, Brent C ^c   Shen, Dinggang ^a,d  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF NORTH CAROLINA   (United States)

^c Department of Teacher Education and Department of Sociology and Anthropology   (United States)

^d Korea University   (South Korea)

Author keywords

Alzheimer's disease (AD); landmark detection; magnetic resonance imaging (MRI); regression forest

Indexed keywords

BRAIN; COMPUTER AIDED DIAGNOSIS; DIAGNOSIS; FEATURE EXTRACTION; FORESTRY; MAGNETIC LEVITATION VEHICLES; MAGNETIC RESONANCE IMAGING; NAVIGATION; SUPPORT VECTOR MACHINES; TISSUE;

ALZHEIMER'S DISEASE; BRAIN TISSUE SEGMENTATIONS; CLASSIFICATION ACCURACY; CLASSIFICATION PERFORMANCE; CONSTRAINED REGRESSION; FEATURE EXTRACTION METHODS; LANDMARK DETECTION; REGRESSION FORESTS;

NEURODEGENERATIVE DISEASES;

ALGORITHM; ALZHEIMER DISEASE; ANATOMIC LANDMARK; ARTICLE; BRAIN REGION; CONTROLLED STUDY; DISEASE CLASSIFICATION; HUMAN; IMAGE ANALYSIS; MAJOR CLINICAL STUDY; MEASUREMENT ACCURACY; MORPHOLOGICAL TRAIT; SUPPORT VECTOR MACHINE; BRAIN; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; REGRESSION ANALYSIS;

ALZHEIMER DISEASE; ANATOMIC LANDMARKS; BRAIN; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; REGRESSION ANALYSIS;

EID: 85006041900     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/TMI.2016.2582386     Document Type: Article

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