Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6067
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dc.contributor.authorZarandi, Mohammad Hossein Fazel-
dc.contributor.authorKhadangi, A.-
dc.contributor.authorKarimi, F.-
dc.contributor.authorTürkşen, İsmail Burhan-
dc.date.accessioned2021-09-11T15:34:52Z-
dc.date.available2021-09-11T15:34:52Z-
dc.date.issued2016en_US
dc.identifier.issn0897-1889-
dc.identifier.issn1618-727X-
dc.identifier.urihttps://doi.org/10.1007/s10278-016-9884-y-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6067-
dc.description.abstractMeniscal tear is one of the prevalent knee disorders among young athletes and the aging population, and requires correct diagnosis and surgical intervention, if necessary. Not only the errors followed by human intervention but also the obstacles of manual meniscal tear detection highlight the need for automatic detection techniques. This paper presents a type-2 fuzzy expert system for meniscal tear diagnosis using PD magnetic resonance images (MRI). The scheme of the proposed type-2 fuzzy image processing model is composed of three distinct modules: Pre-processing, Segmentation, and Classification. lambda-nhancement algorithm is used to perform the pre-processing step. For the segmentation step, first, Interval Type-2 Fuzzy C-Means (IT2FCM) is applied to the images, outputs of which are then employed by Interval Type-2 Possibilistic C-Means (IT2PCM) to perform post-processes. Second stage concludes with re-estimation of "eta" value to enhance IT2PCM. Finally, a Perceptron neural network with two hidden layers is used for Classification stage. The results of the proposed type-2 expert system have been compared with a well-known segmentation algorithm, approving the superiority of the proposed system in meniscal tear recognition.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.ispartofJournal of Digital Imagingen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectExpert systemen_US
dc.subjectComputer-aided diagnosis (CAD)en_US
dc.subjectInterval type-2 fuzzy set theoryen_US
dc.subjectKneeen_US
dc.subjectMeniscus tearen_US
dc.subjectMedical image processingen_US
dc.titleA Computer-Aided Type-II Fuzzy Image Processing for Diagnosis of Meniscus Tearen_US
dc.typeArticleen_US
dc.departmentFaculties, Faculty of Engineering, Department of Industrial Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümütr_TR
dc.identifier.volume29en_US
dc.identifier.issue6en_US
dc.identifier.startpage677en_US
dc.identifier.endpage695en_US
dc.identifier.wosWOS:000393112300008en_US
dc.identifier.scopus2-s2.0-84969776792en_US
dc.institutionauthorTürkşen, İsmail Burhan-
dc.identifier.pmid27198133en_US
dc.identifier.doi10.1007/s10278-016-9884-y-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ2-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeArticle-
item.cerifentitytypePublications-
item.languageiso639-1en-
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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