Non-Euclidean classification of medically imaged objects via s-reps

Medical Image Analysis

Volumn 31, Issue , 2016, Pages 37-45

  Hong, Junpyo ^a   Vicory, Jared ^a   Schulz, Jörn ^d   Styner, Martin ^a,c   Marron, J S ^b   Pizer, Stephen M ^a  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b University of North Carolina at Chapel Hill   (United States)

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

^d STAVANGER UNIVERSITY HOSPITAL   (Norway)

Author keywords

Pattern classification; Shape analysis; Statistical analysis

Indexed keywords

GEOMETRY; MEDICAL IMAGING; PATTERN RECOGNITION; STATISTICAL METHODS;

CLASSIFICATION METHODS; CLASSIFICATION SCHEME; DISCRIMINATIVE POWER; EUCLIDEANIZATION; GEOMETRIC OBJECTS; HEALTHY CONTROLS; RECEIVER OPERATOR CHARACTERISTIC CURVES; SHAPE ANALYSIS;

IMAGE CLASSIFICATION;

ARTICLE; CLASSIFICATION; CONTROLLED STUDY; DIAGNOSTIC IMAGING; HIPPOCAMPUS; HUMAN; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SCHIZOPHRENIA; STATISTICAL ANALYSIS; SUPPORT VECTOR MACHINE; ALGORITHM; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; EVALUATION STUDY; IMAGE ENHANCEMENT; MACHINE LEARNING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; HIPPOCAMPUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MACHINE LEARNING; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SCHIZOPHRENIA; SENSITIVITY AND SPECIFICITY;

EID: 84959460983     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2016.01.007     Document Type: Article

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