A cost-sensitive extension of AdaBoost with markov random field priors for automated segmentation of breast tumors in ultrasonic images

International Journal of Computer Assisted Radiology and Surgery

Volumn 5, Issue 5, 2010, Pages 537-547

  Takemura, Atsushi ^a   Shimizu, Akinobu ^a   Hamamoto, Kazuhiko ^b  

^a TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY   (Japan)

^b TOKAI UNIVERSITY   (Japan)

Author keywords

AdaBoost; Breast tumor; Cost sensitive extension; Segmentation; Ultrasonic image

Indexed keywords

ALGORITHM; ARTICLE; AUTOMATION; BREAST CARCINOMA; BREAST CYST; BREAST FIBROADENOMA; BREAST TUMOR; CONTROLLED STUDY; DIAGNOSTIC IMAGING; ECHOMAMMOGRAPHY; HIDDEN MARKOV MODEL; HUMAN; IMAGE ANALYSIS; IMAGE DISPLAY; IMAGE PROCESSING; MAJOR CLINICAL STUDY; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; VALIDATION PROCESS;

EID: 77958152423     PISSN: 18616410     EISSN: 18616429     Source Type: Journal    
DOI: 10.1007/s11548-010-0411-1     Document Type: Article

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