Yapısal Benzerlik İndeksini Kullanarak Kolonoskopi Videolarında Değişim Anlarının Belirlenmesi

dc.contributor.author Kacmaz, Rukiye Nur
dc.contributor.author Yilmaz, Bulent
dc.date.accessioned 2025-09-25T10:37:11Z
dc.date.available 2025-09-25T10:37:11Z
dc.date.issued 2018
dc.description.abstract The aim of this study is to reduce the number of images extracted from the videos recorded by the specialists during the colonoscopy process for further examination, thereby enabling the specialist to deal with fewer images. Since the images obtained from the videos are very similar, the main assumption of this study is that the whole video can be represented by fewer images. The approach used in this study is the structural similarity index. Totally, images were obtained from 4 different videos coming from healthy, ulcerative colitis, Crohn's, and polyp patients. The noisy images in these videos were eliminated manually. When the structural similarity index between two consecutive clear images was less than 0.83, the second image was selected and shown to the specialist for his/her examination. By this way, the frames carrying significantly new information from the videos were defined as the variation instances. The tests on healthy or diseased colon videos showed that only 5-10% of the clear images provide significantly new information. en_US
dc.identifier.doi 10.1109/TIPTEKNO.2018.8597137
dc.identifier.isbn 9781538668528
dc.identifier.scopus 2-s2.0-85061759911
dc.identifier.uri https://doi.org/10.1109/TIPTEKNO.2018.8597137
dc.identifier.uri https://hdl.handle.net/20.500.12573/2932
dc.language.iso tr en_US
dc.publisher IEEE en_US
dc.relation.ispartof Medical Technologies National Congress (TIPTEKNO) -- NOV 08-10, 2018 -- Magusa, CYPRUS en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Colonoscopy en_US
dc.subject Image Processing en_US
dc.subject Structural Similarity Index en_US
dc.title Yapısal Benzerlik İndeksini Kullanarak Kolonoskopi Videolarında Değişim Anlarının Belirlenmesi en_US
dc.title.alternative Detection of Variation Instances on Colonoscopy Videos Using Structural Similarity Index en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.scopusid 57202288551
gdc.author.scopusid 57189925966
gdc.author.wosid Yılmaz, Bülent/Acr-8602-2022
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gdc.description.department Abdullah Gül University en_US
gdc.description.departmenttemp [Kacmaz, Rukiye Nur] Abdullah Gul Univ, Elect & Comp Engn Dept, Kayseri, Turkey; [Yilmaz, Bulent] Abdullah Gul Univ, Elect Elect Engn Dept, Kayseri, Turkey en_US
gdc.description.endpage 4
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 1
gdc.description.woscitationindex Conference Proceedings Citation Index - Science
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gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
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