Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSutasinee Thovutikulen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.description.abstractBreast 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 develop a system that helps radiologists to detect microcalcification in mammograms. In particular, we apply the interval type-2 fuzzy logic system with four features, i.e., B-descriptor, D-descriptor, average intensity inside boundary, and intensity difference between inside and outside boundaries. We also compare the result with the result from a type-1 Mamdani fuzzy inference system with the same set of features. The result from the type-1 fuzzy logic system yields 87.95% correct classification with 11.33 false positives per image whereas interval type-2 fuzzy logic system provides 90.36% correct classification with only 4.73 false positives per image. © 2007 IEEE.en_US
dc.subjectComputer Scienceen_US
dc.titleMicrocalcification detection in mammograms using interval type-2 fuzzy logic systemen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleIEEE International Conference on Fuzzy Systemsen_US Mai Universityen_US
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.