Interactive segmentation in multimodal medical imagery using a bayesian transductive learning approach

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7260, Issue , 2009, Pages

  Lee, Noah ^a   Caban, Jesus ^b   Ebadollahi, Shahram ^b   Laine, Andrew ^a  

^a Heffner Biomedical Imaging Laboratory   (United States)

^b IBM T J WATSON RESEARCH CENTER   (United States)

Author keywords

Brain; Classifier design; Machine learning; Observer studies; Segmentation

Indexed keywords

BAYES ALGORITHMS; BAYES MODELS; BAYESIAN; BRAIN IMAGERY; CLASS LABELS; CLASSIFIER DESIGN; CONDITIONAL DISTRIBUTION; CONDITIONAL INDEPENDENCE ASSUMPTION; CONDITIONAL INDEPENDENCES; COVARIATE; FEATURE DIMENSIONS; FEATURE SPACE; INTERACTIVE SEGMENTATION; LABEL INFORMATION; LABELED DATA; LABELED TRAINING DATA; MACHINE LEARNING; MEDICAL DOMAINS; MEDICAL IMAGERY; MULTI-MODAL; MULTIMODAL MEDICAL IMAGES; NOVEL ALGORITHM; OBSERVER STUDIES; PARAMETER SPACES; SEGMENTATION; SEGMENTATION PERFORMANCE; SEMI-SUPERVISED LEARNING; SENSITIVITY AND SPECIFICITY; SPATIAL CLASSIFICATION; TEST SETS; TRANSDUCTIVE LEARNING;

CLASSIFIERS; COMPUTER AIDED DIAGNOSIS; EDUCATION; IMAGE CLASSIFICATION; INFERENCE ENGINES; LABELS; MACHINE DESIGN; MEDICAL IMAGING; PARAMETER ESTIMATION; ROBOT LEARNING; SUPERVISED LEARNING;

LEARNING ALGORITHMS;

EID: 66749160345     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.811675     Document Type: Conference Paper

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