Segmentation of Abdominal Organs From Mr Images Using Multi-Level Hierarchical Classification

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.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.identifier.issn 1300-1884
dc.identifier.issn 1304-4915
dc.identifier.scopus 2-s2.0-84942924883
dc.identifier.uri https://hdl.handle.net/20.500.14365/2900
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
dspace.entity.type Publication
gdc.author.id Kavur, Ali Emre/0000-0002-9328-8140
gdc.author.id Selver, M. Alper/0000-0002-8445-0388
gdc.author.wosid Kavur, Ali Emre/B-9569-2016
gdc.author.wosid Selver, M. Alper/V-5118-2019
gdc.author.wosid Selver, Alper/AAN-1987-2021
gdc.author.wosid Dicle, oğuz/AFM-0858-2022
gdc.coar.access metadata only access
gdc.coar.type text::journal::journal article
gdc.description.department İzmir Ekonomi Üniversitesi en_US
gdc.description.departmenttemp [Selvi, Esref; Kavur, Ali Emre] Dokuz Eylul Univ, Fen Bilimleri Enstitusu, Izmir, Turkey; [Selver, M. Alper] Dokuz Eylul Univ, Muhendislik Fak, Elekt Elekt Muhendisligi Bolumu, Izmir, Turkey; [Guzelis, Cuneyt] Izmir Econ Univ, Muhendislik Fak, Elekt Elekt Muhendisligi Bolumu, Izmir, Turkey; [Dicle, Oguz] Dokuz Eylul Univ, Tip Fak, Radyol Anabilimdali, Izmir, Turkey en_US
gdc.description.endpage 546 en_US
gdc.description.issue 3 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q3
gdc.description.startpage 533 en_US
gdc.description.volume 30 en_US
gdc.description.wosquality Q3
gdc.identifier.wos WOS:000367386500020
gdc.index.type WoS
gdc.index.type Scopus
gdc.scopus.citedcount 21
gdc.wos.citedcount 19
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relation.isOrgUnitOfPublication.latestForDiscovery e9e77e3e-bc94-40a7-9b24-b807b2cd0319

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