A multiresolution stochastic level set method for Mumford-Shah image segmentation

IEEE Transactions on Image Processing

Volumn 17, Issue 12, 2008, Pages 2289-2300

  Law, Yan Nei ^b   Lee, Hwee Kuan ^b   Yip, Andy M ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b BIOINFORMATICS INSTITUTE   (Singapore)

Author keywords

Basin hopping; Global optimization; Image segmentation; Mumford Shah model; Region splitting and merging; Stochastic level set method

Indexed keywords

DIGITAL IMAGE STORAGE; DROP BREAKUP; IMAGE PROCESSING; IMAGE SEGMENTATION; LEVEL MEASUREMENT; MULTIRESOLUTION ANALYSIS; OPTIMIZATION; SIMULATED ANNEALING; STOCHASTIC MODELS;

BASIN HOPPING; COMPUTATIONAL COSTS; GLOBAL MINIMUMS; GLOBAL OPTIMAL SOLUTIONS; GRADIENT BASED; GRADIENT DESCENTS; HYBRID APPROACHES; IMAGE SEGMENTATION MODELS; INITIAL GUESSES; LEVEL SET METHODS; LOCAL MINIMUMS; LOCAL TRAPS; MULTIRESOLUTION; MULTIRESOLUTION APPROACHES; MUMFORD-SHAH MODEL; PIECEWISE CONSTANTS; PRACTICAL SOLUTIONS; QUALITY SOLUTIONS; REGION SPLITTING AND MERGING; SPATIAL RESOLUTIONS; STOCHASTIC LEVEL SET METHOD; STOCHASTIC METHODS; STOCHASTIC OPTIMIZATION METHODS;

GLOBAL OPTIMIZATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; STATISTICS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STOCHASTIC PROCESSES;

EID: 57049189180     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2008.2005823     Document Type: Article

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