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dc.contributor.authorKornkamon Suttitanawaten_US
dc.contributor.authorApinun Uppanunen_US
dc.contributor.authorSansanee Auephanwiriyakulen_US
dc.contributor.authorNipon Theera-Umponen_US
dc.contributor.authorPatiwet Wuttisarnwattanaen_US
dc.date.accessioned2019-08-05T04:33:37Z-
dc.date.available2019-08-05T04:33:37Z-
dc.date.issued2019-04-08en_US
dc.identifier.other2-s2.0-85065023881en_US
dc.identifier.other10.1109/ICCSCE.2018.8684996en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065023881&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/65459-
dc.description.abstract© 2018 IEEE. Lung nodule detection is a crucial task in lung cancer examination since early detection may lead to more successful treatment. In this work, a novel lung nodule detection algorithm based upon the interval type-2 fuzzy logic system is proposed. The method utilizes four features consisting of D-descriptors, the average intensity of the inside boundary, the circularity ratio, and HH diagonal component from the wavelet transform. The proposed method can promisingly detect the probable locations of nodules. The system produces 0.82 of true positive rate with 13.11 false positives per image.en_US
dc.subjectChemical Engineeringen_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.subjectMathematicsen_US
dc.titleLung nodule detection from chest X-ray images using interval type-2 fuzzy logic systemen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings - 8th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2018en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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