Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/65459
Title: Lung nodule detection from chest X-ray images using interval type-2 fuzzy logic system
Authors: Kornkamon Suttitanawat
Apinun Uppanun
Sansanee Auephanwiriyakul
Nipon Theera-Umpon
Patiwet Wuttisarnwattana
Keywords: Chemical Engineering
Computer Science
Engineering
Mathematics
Issue Date: 8-Apr-2019
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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065023881&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/65459
Appears in Collections:CMUL: Journal Articles

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