Class-specific weighting for Markov random field estimation: Application to medical image segmentation

Medical Image Analysis

Volumn 16, Issue 8, 2012, Pages 1477-1489

  Monaco, James P ^a   Madabhushi, Anant ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

Digital pathology; Histology; Magnetic resonance imaging; Markov random fields; Prostate cancer detection

Indexed keywords

4 TESLA; A-POSTERIORI PROBABILITIES; BAYESIAN CLASSIFIER; BRAIN MR; CLASSIFICATION SYSTEM; CLASSIFICATION TASKS; CLASSIFIER PERFORMANCE; CURRENT ESTIMATION; EX-VIVO; EXHAUSTIVE SEARCH; HISTOLOGICAL SECTION; ITERATED CONDITIONAL MODES; MAP ESTIMATION; MAP ESTIMATOR; MARGINALS; MARKOV CHAIN MONTE CARLO METHOD; MARKOV RANDOM FIELDS; MAXIMUM A POSTERIORI ESTIMATION; MEDICAL IMAGE SEGMENTATION; MONTE CARLO; OPERATING POINTS; OPTIMAL CLASSIFICATION; PROSTATE CANCER DETECTION; RADICAL PROSTATECTOMY; RECEIVER OPERATOR CHARACTERISTIC CURVES; THRESHOLDING; WEIGHTED MAP;

COST FUNCTIONS; HISTOLOGY; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MEDICAL IMAGE PROCESSING; MONTE CARLO METHODS; UROLOGY;

ESTIMATION;

ARTICLE; CLASSIFIER; COST BENEFIT ANALYSIS; HUMAN; HUMAN TISSUE; IMAGE ANALYSIS; MALE; MARKOV RANDOM FIELD; MONTE CARLO METHOD; MULTIPLICATIVE WEIGHTED MAXIMUM A POSTERIORI; MULTIPLICATIVE WEIGHTED MAXIMUM POSTERIOR MARGINAL; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIORITY JOURNAL; PROBABILITY; PROSTATE CARCINOMA; PROSTATECTOMY; SENSITIVITY AND SPECIFICITY; STATISTICAL PARAMETERS;

HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MARKOV CHAINS; MONTE CARLO METHOD; PROSTATIC NEOPLASMS; ROC CURVE;

EID: 84870065068     PISSN: 13618415     EISSN: 13618423     Source Type: Journal    
DOI: 10.1016/j.media.2012.06.007     Document Type: Article

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