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DC Field | Value | Language |
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dc.contributor.author | Kornkamon Suttitanawat | en_US |
dc.contributor.author | Apinun Uppanun | en_US |
dc.contributor.author | Sansanee Auephanwiriyakul | en_US |
dc.contributor.author | Nipon Theera-Umpon | en_US |
dc.contributor.author | Patiwet Wuttisarnwattana | en_US |
dc.date.accessioned | 2019-08-05T04:33:37Z | - |
dc.date.available | 2019-08-05T04:33:37Z | - |
dc.date.issued | 2019-04-08 | en_US |
dc.identifier.other | 2-s2.0-85065023881 | en_US |
dc.identifier.other | 10.1109/ICCSCE.2018.8684996 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065023881&origin=inward | en_US |
dc.identifier.uri | http://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.subject | Chemical Engineering | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.subject | Mathematics | en_US |
dc.title | Lung nodule detection from chest X-ray images using interval type-2 fuzzy logic system | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | Proceedings - 8th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2018 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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