Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14365/2900
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Selvi, Esref | - |
dc.contributor.author | Selver, M. Alper | - |
dc.contributor.author | Kavur, Ali Emre | - |
dc.contributor.author | Guzelis, Cuneyt | - |
dc.contributor.author | Dicle, Oguz | - |
dc.date.accessioned | 2023-06-16T14:50:39Z | - |
dc.date.available | 2023-06-16T14:50:39Z | - |
dc.date.issued | 2015 | - |
dc.identifier.issn | 1300-1884 | - |
dc.identifier.issn | 1304-4915 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14365/2900 | - |
dc.description.abstract | Medical imaging modalities can provide very detailed and informative mappings of the anatomy of a subject. These detailed and informative mappings can be processed to extract the information of interest instead of dealing with whole data (segmentation). Since manual segmentation on each slice is time consuming, tedious and operator dependent, automatic tools and techniques are needed. Segmentation of abdominal organs is a very challenging field of application due to overlapping intensity ranges of the organs, variations in human anatomy and pathology and the number of studies is very limited for Magnetic Resonance (MR), which is a relatively newer and rapidly developing imaging modality. Since it is obligatory to analyze and visualize MR images of abdominal organs (i.e. liver, right/left kidneys, spleen, pancreas, gall bladder) for several medical procedures, the main goal of this paper is to design and develop a segmentation system (method+software), which is robust to the challenges mentioned above, adaptive to the properties of the abdominal organs as well as to the interrelationships of these organs. | en_US |
dc.language.iso | tr | en_US |
dc.publisher | Gazi Univ, Fac Engineering Architecture | en_US |
dc.relation.ispartof | Journal of the Faculty of Engıneerıng And Archıtecture of Gazı Unıversıty | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Segmentation | en_US |
dc.subject | MR | en_US |
dc.subject | hierarchical classification | en_US |
dc.subject | abdomen | en_US |
dc.subject | Combining Multiple Classifiers | en_US |
dc.subject | Automatic Segmentation | en_US |
dc.subject | Neural-Network | en_US |
dc.subject | Ct | en_US |
dc.subject | Atlas | en_US |
dc.subject | Recognition | en_US |
dc.title | Segmentation of abdominal organs from MR images using multi-level hierarchical classification | en_US |
dc.title.alternative | Batin bölgesi organlarinin mr görüntülerinden çok aşamali hiyerarşik siniflama ile bölütlenmesi | en_US |
dc.type | Article | en_US |
dc.identifier.scopus | 2-s2.0-84942924883 | en_US |
dc.department | İzmir Ekonomi Üniversitesi | en_US |
dc.authorid | Kavur, Ali Emre/0000-0002-9328-8140 | - |
dc.authorid | Selver, M. Alper/0000-0002-8445-0388 | - |
dc.authorwosid | Kavur, Ali Emre/B-9569-2016 | - |
dc.authorwosid | Selver, M. Alper/V-5118-2019 | - |
dc.authorwosid | Selver, Alper/AAN-1987-2021 | - |
dc.authorwosid | Dicle, oğuz/AFM-0858-2022 | - |
dc.identifier.volume | 30 | en_US |
dc.identifier.issue | 3 | en_US |
dc.identifier.startpage | 533 | en_US |
dc.identifier.endpage | 546 | en_US |
dc.identifier.wos | WOS:000367386500020 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.identifier.scopusquality | Q2 | - |
item.openairetype | Article | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
item.fulltext | With Fulltext | - |
item.grantfulltext | reserved | - |
item.languageiso639-1 | tr | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Files in This Item:
File | Size | Format | |
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2075.pdf Restricted Access | 2.52 MB | Adobe PDF | View/Open Request a copy |
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