Population-based incremental interactive concept learning for image retrieval by stochastic string segmentations

IEEE Transactions on Medical Imaging

Volumn 23, Issue 6, 2004, Pages 676-689

  Ghebreab, Sennay ^a   Jaffe, C Carl ^b   Smeulders, Arnold W M ^c  

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

Content based image retrieval; Multifeature object description; Population based incremental learning; Relevance feedback; Visual concept learning

Indexed keywords

DATABASE SYSTEMS; DISCRETE TIME CONTROL SYSTEMS; FUNCTIONS; IMAGE RETRIEVAL; INTEGRATION; INTERPOLATION; LEAST SQUARES APPROXIMATIONS; RANDOM PROCESSES; SEMANTICS; VECTORS;

CONTENT-BASED IMAGE RETRIEVAL; MULTIFEATURE OBJECT DESCRIPTIONS; POPULATION-BASED INCREMENTAL LEARNING; RELEVANCE FEEDBACK; VISUAL CONCEPT LEARNING;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; CERVICAL SPINE; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; DATA BASE; EVALUATION; HUMAN; INFORMATION RETRIEVAL; MEDICAL RECORD; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; STATISTICS; VALIDATION STUDY;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CERVICAL VERTEBRAE; DATABASE MANAGEMENT SYSTEMS; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; STOCHASTIC PROCESSES;

EID: 2942576146     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2004.826942     Document Type: Article

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