Automated detection and classification of breast tumors.
This paper presents a new method for the mammographic detection and classification of two types of breast tumors, stellate lesions and circumscribed lesions. The method assumes that both types of tumors appear as approximately circular, bright masses with a fuzzy boundary and that stellate lesions are in addition surrounded by a radiating structure of sharp, fine lines. Experimental results for a set of 27 mammograms are presented and the method is shown to have a high detection rate and an extremely low false positive rate.
Ng
S L
SL
Department of Computing Science, University of Alberta, Edmonton, Canada.
Bischof
W F
WF
D001331:Automation; D001943:Breast Neoplasms / Q000145:classification / Q000000981:diagnostic imaging*; D006801:Humans; D008327:Mammography / Q000379:methods*; D008433:Mathematics; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D012680:Sensitivity and Specificity