A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 32, Issue 1, 2010, Pages 30-44

  Yang, Liu ^a   Jin, Rong ^b   Mummert, Lily ^c   Sukthankar, Rahul ^c   Goode, Adam ^a   Zheng, Bin ^d   Hoi, Steven C H ^e   Satyanarayanan, Mahadev ^a  

^a Carnegie Mellon University   (United States)

^b Michigan State University   (United States)

^c INTEL CORPORATION   (United States)

^d UNIVERSITY OF PITTSBURGH MEDICAL CENTER   (United States)

^e NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Boosting; Distance metric learning; Image retrieval; Machine learning

Indexed keywords

BINARY REPRESENTATIONS; BOOSTING; BOOSTING ALGORITHM; COMPUTATIONAL COSTS; CONTENT-BASED IMAGE RETRIEVAL SYSTEM; CRITICAL COMPONENT; DECISION SUPPORTS; DISTANCE FUNCTIONS; DISTANCE METRIC LEARNING; DISTANCE METRICS; IMAGE DATASETS; IMAGE RETRIEVAL SYSTEMS; IMAGECLEF; LEAD USERS; MAMMOGRAPHIC IMAGES; MEDICAL IMAGE RETRIEVAL; MEDICAL IMAGES; MEDICAL PROFESSIONALS; QUERY IMAGES; RETRIEVAL PERFORMANCE; SEMANTIC ANNOTATIONS; SEMANTIC SIMILARITY; SIDE INFORMATION; SIMILAR IMAGE; SIMILARITY MEASUREMENTS; STATE-OF-THE-ART APPROACH; VISUAL APPEARANCE; VISUAL RESEMBLANCE;

ADAPTIVE BOOSTING; ALGORITHMS; CONTENT BASED RETRIEVAL; DECISION SUPPORT SYSTEMS; DIAGNOSIS; HAMMING DISTANCE; IMAGE RETRIEVAL; INFORMATION RETRIEVAL; LEARNING SYSTEMS; MAMMOGRAPHY; SEMANTICS;

SEARCH ENGINES;

ALGORITHM; AREA UNDER THE CURVE; ARTICLE; ARTIFICIAL INTELLIGENCE; DIAGNOSTIC IMAGING; FACTUAL DATABASE; IMAGE PROCESSING; INFORMATION RETRIEVAL; MAMMOGRAPHY; MEDICAL INFORMATICS; METHODOLOGY; PRINCIPAL COMPONENT ANALYSIS; RADIOGRAPHY; SEMANTICS;

ALGORITHMS; AREA UNDER CURVE; ARTIFICIAL INTELLIGENCE; DATABASES, FACTUAL; DIAGNOSTIC IMAGING; IMAGE PROCESSING, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MAMMOGRAPHY; MEDICAL INFORMATICS; PRINCIPAL COMPONENT ANALYSIS; RADIOGRAPHY; SEMANTICS;

EID: 74949118977     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2008.273     Document Type: Article

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