Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/224
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dc.contributor.authorBarstuğan, Mücahid-
dc.contributor.authorCeylan, Rahime-
dc.contributor.authorAsoğlu, Semih-
dc.contributor.authorCebeci, Hakan-
dc.contributor.authorKoplay, Mustafa-
dc.date.accessioned2021-12-13T10:23:53Z-
dc.date.available2021-12-13T10:23:53Z-
dc.date.issued2019-
dc.identifier.isbn9781728137896-
dc.identifier.urihttps://doi.org/10.1109/ISMSIT.2019.8932938-
dc.identifier.urihttps://hdl.handle.net/20.500.13091/224-
dc.description3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 -- 11 October 2019 through 13 October 2019 -- -- 156063en_US
dc.description.abstractAdrenal tumors occur on adrenal glands and can be malignant. Adrenal glands consist of cortex and medulla. If cortex or medulla produce hormones extremely, the hormonal unbalance situation arises. This situation causes adrenal tumor occurrence on adrenal glands. In this study, adrenal tumors on T1 and T2-weighted MR images were classified by the SVM algorithm. Before the classification stage, different feature extraction algorithms and filtering methods were used for preprocessing. The classification results that were obtained by four different methods were evaluated on five different evaluation metrics as sensitivity, specificity, accuracy, precision, and F-score. The best classification performance was obtained with Method 2 on T1-weighted MR (Magnetic Resonance) images where the sensitivity, specificity, accuracy, precision, and F-score metrics were obtained as 99.17%, 90%, 98.4%, 99.17%, and 99.13%, respectively. © 2019 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Proceedingsen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAdrenal glanden_US
dc.subjectadrenal tumoren_US
dc.subjectclassificationen_US
dc.subjectfeature extractionen_US
dc.subjectimage filteringen_US
dc.subjectMR imageen_US
dc.titleAdrenal Tumor Classification on T1 and T2-weighted Abdominal MR Imagesen_US
dc.typeConference Objecten_US
dc.identifier.doi10.1109/ISMSIT.2019.8932938-
dc.identifier.scopus2-s2.0-85078035370en_US
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik-Elektronik Mühendisliği Bölümüen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.authorscopusid57200139642-
dc.authorscopusid12244684600-
dc.authorscopusid57203019010-
dc.authorscopusid56033553000-
dc.authorscopusid55920818900-
item.cerifentitytypePublications-
item.grantfulltextembargo_20300101-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeConference Object-
item.fulltextWith Fulltext-
crisitem.author.dept02.04. Department of Electrical and Electronics Engineering-
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
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