Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions

IEEE Transactions on Medical Imaging

Volumn 22, Issue 2, 2003, Pages 155-169

  Madabhushi, Anant ^a   Metaxas, Dimitris N ^b  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b RUTGERS UNIVERSITY   (United States)

Author keywords

Automatic segmentation; Boundary; Breast; Deformable model; Directional gradient; Intensity; Medical; Seed point; Texture; Tumor; Ultrasound

Indexed keywords

IMAGE SEGMENTATION; MAMMOGRAPHY; MATHEMATICAL MODELS; ONCOGENIC VIRUSES; PROBABILITY; TUMORS; ULTRASONIC IMAGING;

AUTOMATED SEGMENTATION; BREAST CANCER DIAGNOSIS; DEFORMABLE SHAPE BASED MODEL; SPECKLE NOISE;

MEDICAL IMAGING;

ALGORITHM; ANATOMY; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BREAST TUMOR; CLASSIFICATION; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; ECHOGRAPHY; ECHOMAMMOGRAPHY; EVALUATION; FEMALE; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; PREDICTION AND FORECASTING; REPRODUCIBILITY; SIGNAL PROCESSING; THREE DIMENSIONAL IMAGING; VALIDATION STUDY;

ALGORITHMS; ANATOMY, CROSS-SECTIONAL; ARTIFICIAL INTELLIGENCE; BREAST NEOPLASMS; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; PATTERN RECOGNITION, AUTOMATED; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; SIGNAL PROCESSING, COMPUTER-ASSISTED; ULTRASONOGRAPHY, MAMMARY;

EID: 0038398643     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2002.808364     Document Type: Article

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