Abdominal image segmentation on Android based mobile devices

dc.contributor.authorTuncer, Seda Arslan
dc.contributor.authorAlkan, Ahmet
dc.date.accessioned2026-08-12T16:08:26Z
dc.date.issued2014
dc.departmentFırat Üniversitesi
dc.description2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 -- 23 April 2014 through 25 April 2014 -- Trabzon -- 106053
dc.description.abstractMedical services have a great importance in international development. Hospitals have been forced to reinforce their health services and technological infrastructure developments because of the rapid development of information technology. Liver segmentation is a difficult task because of its variable shape it can be thought as a large footprint. In addition, the nearness of its color and texture to surrounding organs tissues makes its boundaries unclear. In this study, computed tomography images have been used to segment the liver that was the first part of the lesion liver detection. Obtained liver segmentation result achievements have been compared with the manual segmentation of the radiologists. Segmentation accuracies have been assessed by using Zijdenbos similarity index. The applied methodology achieved approximately 93% segmentation accuracy. After liver segmentation stage, this segmentation procedure is located on mobile environment that medical experts can access the software with their mobile devices. This is the first part of the ongoing decision support system study that can be used to define diagnostic lesions on the liver via android-based mobile devices. © 2014 IEEE.
dc.identifier.doi10.1109/SIU.2014.6830352
dc.identifier.endpage809
dc.identifier.isbn978-147994874-1
dc.identifier.scopus2-s2.0-84903776758
dc.identifier.scopusqualityN/A
dc.identifier.startpage806
dc.identifier.urihttps://doi.org/10.1109/SIU.2014.6830352
dc.identifier.urihttps://hdl.handle.net/11508/41231
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIEEE Computer Society
dc.relation.ispartof2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectArtificial intelligence; Computerized tomography; Decision support systems; Image segmentation; Information technology; Mobile devices; Signal processing; Computed tomography images; International development; Liver segmentation; Manual segmentation; Mobile environments; Segmentation accuracy; Segmentation procedure; Technological infrastructure; Android (operating system)
dc.titleAbdominal image segmentation on Android based mobile devices
dc.title.alternativeAndroid işletim sistemli mobil cihazlarda abdominal görüntü bölütleme
dc.typeConference Object

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