Gelişmiş Arama

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dc.contributor.authorİsoğlu, Selinen_US
dc.contributor.authorKoca Işıkçı, Elifen_US
dc.contributor.authorDuru, Dilek Gökselen_US
dc.date.accessioned2019-07-23T11:15:10Z
dc.date.available2019-07-23T11:15:10Z
dc.date.issued2017en_US
dc.identifier.citationIsoglu, S., Koca, E. I., Duru, D. G., & Ieee. (2017). Comparative Multiple Sclerosis Lesion Segmentation in Magnetic Resonance Images. New York: Ieee.en_US
dc.identifier.isbn9781538604403
dc.identifier.urihttps://hdl.handle.net/20.500.12294/1582
dc.descriptionİsoğlu, Selin (Arel Author), Koca Işıkçı, Elif (Arel Author),Duru, Dilek Göksel (Arel Author)en_US
dc.description.abstractIn this study, the unsupervised clustering method namely K-means algorithm is applied for identifying the multiple sclerosis (MS) lesions in magnetic resonance (MR) images automatically. MS lesion detection is essential for diagnosing the disease and monitoring its progression. The automated method aims to eliminate user-dependent classification errors and to improve computational capacity in detecting more reliable MS segmentation results. K-means algorithm that relies on k cluster number on data is addressed to determine lesions in pathological brain MR images. Comparative segmentation is aimed by generating an in-house developed binary image segmentation routine in MATLAB. Segmented regions are compared to the results of K-means algorithm with respect to the predefined ROIs of lesions. The proposed K-means lesion detection routine is applied on real brain MR images and the results are qualitatively compared, and the method manages to locate the lesions successfully.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.ispartof2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectSegmentationen_US
dc.subjectK-meansen_US
dc.subjectMultiple Sclerosisen_US
dc.titleComparative Multiple Sclerosis Lesion Segmentation in Magnetic Resonance Imagesen_US
dc.typeconferenceObjecten_US
dc.departmentMühendislik ve Mimarlık Fakültesi, Biyomedikal Mühendisliği Bölümüen_US
dc.authorid0000-0003-1484-8603en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.coverage.doi10.1109/EBBT.2017.7956784


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