Completely automated segmentation approach for breast ultrasound images using multiple-domain features

Ultrasound in Medicine and Biology

Volumn 38, Issue 2, 2012, Pages 262-275

  Shan, Juan ^a   Cheng, H D ^a   Wang, Yuxuan ^a  

^a Utah State University ^*  (United States)

Author keywords

Breast ultrasound segmentation; CAD (computer aided diagnosis); Distance feature; Phase feature; Region of interest (ROI)

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AUTOMATED SEGMENTATION; BREAST ULTRASOUND; COMPUTER AIDED DIAGNOSIS SYSTEMS; DISTANCE FEATURE; GENERATION METHOD; PHASE FEATURES; RADIAL DISTANCE; REGION OF INTEREST; SEGMENTATION METHODS;

IMAGE SEGMENTATION; MEDICAL IMAGING; NEURAL NETWORKS; SENSITIVITY ANALYSIS; ULTRASONIC APPLICATIONS; ULTRASONICS;

COMPUTER AIDED DIAGNOSIS;

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED SEGMENTATION APPROACH; BREAST CANCER; BREAST TUMOR; COMPUTER ASSISTED DIAGNOSIS; CONTROLLED STUDY; ECHOMAMMOGRAPHY; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MAJOR CLINICAL STUDY; PRIORITY JOURNAL; RADIOLOGICAL PROCEDURES; SCORING SYSTEM; SENSITIVITY ANALYSIS; ULTRASOUND SCANNER;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BREAST NEOPLASMS; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; ULTRASONOGRAPHY, MAMMARY;

EID: 84862926199     PISSN: 03015629     EISSN: 1879291X     Source Type: Journal    
DOI: 10.1016/j.ultrasmedbio.2011.10.022     Document Type: Article

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