A multichannel markov random field framework for tumor segmentation with an application to classification of gene expression-based breast cancer recurrence risk

IEEE Transactions on Medical Imaging

Volumn 32, Issue 4, 2013, Pages 637-648

  Ashraf, Ahmed B ^a   Gavenonis, Sara C ^a   Daye, Dania ^a   Mies, Carolyn ^a   Rosen, Mark A ^a   Kontos, Despina ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Breast cancer recurrence prediction; breast dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI); breast tumor segmentation; tumor characterization

Indexed keywords

BREAST CANCER; BREAST TUMOR; CONDITIONAL INDEPENDENCE ASSUMPTION; DYNAMIC CONTRAST ENHANCED MAGNETIC RESONANCE IMAGING; MAGNETIC RESONANCE IMAGING (MRI); RECEIVER OPERATING CHARACTERISTICS; SUPPORT VECTOR MACHINE CLASSIFIERS; TUMOR CHARACTERIZATION;

ALGORITHMS; DISEASES; FEATURE EXTRACTION; GENE EXPRESSION; IMAGE SEGMENTATION; MAGNETIC RESONANCE IMAGING; MARKOV PROCESSES;

TUMORS;

ESTROGEN RECEPTOR; GADOBENATE DIMEGLUMINE; GADODIAMIDE;

ALGORITHM; ARTICLE; BREAST CANCER; CANCER ADJUVANT THERAPY; CANCER RISK; COMPARATIVE STUDY; CONTRAST ENHANCEMENT; FEMALE; GENE EXPRESSION; HUMAN; HUMAN TISSUE; MAJOR CLINICAL STUDY; MULTICHANNEL MARKOV RANDOM FIELD FRAMEWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PRIMARY TUMOR; RADIOLOGIST; REVERSE TRANSCRIPTION POLYMERASE CHAIN REACTION; TUMOR GROWTH;

AREA UNDER CURVE; BREAST NEOPLASMS; COMPUTATIONAL BIOLOGY; FEMALE; GENE EXPRESSION PROFILING; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; KINETICS; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; NEOPLASM RECURRENCE, LOCAL; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; ROC CURVE; SUPPORT VECTOR MACHINES;

EID: 84875993482     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2012.2219589     Document Type: Article

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