Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/50705
Title: Microcalcification detection in mammograms using interval type-2 fuzzy logic system with automatic membership function generation
Authors: Suraphon Chumklin
Sansanee Auephanwiriyakul
Nipon Theera-Umpon
Keywords: Computer Science
Issue Date: 25-Nov-2010
Abstract: Breast cancer is an important deleterious disease. Mortality rate from this cancer is effectively high and rapidly increasing. The detection at the earlier state can help to reduce the mortality rate. In this paper, we apply the interval type-2 fuzzy system with automatic membership function generation using the Possibilistic C-Means (PCM) clustering algorithm. We utilize four features, i.e., B-descriptor, D-descriptor, average intensity of the inside boundary, and intensity difference between the inside and the outside boundaries. We also compare the result with the result from the interval type-2 fuzzy logic system with automatic membership function generation using the Fuzzy C-Means (FCM) clustering algorithm. The interval type-2 fuzzy system with PCM membership functions generation yields the best result, i.e., 89.47% correct classification with only 6 false positives per image. © 2010 IEEE.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78549276188&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/50705
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.