Abdominal image segmentation on Android based mobile devices
| dc.contributor.author | Tuncer, Seda Arslan | |
| dc.contributor.author | Alkan, Ahmet | |
| dc.date.accessioned | 2026-08-12T16:08:26Z | |
| dc.date.issued | 2014 | |
| dc.department | Fırat Üniversitesi | |
| dc.description | 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 -- 23 April 2014 through 25 April 2014 -- Trabzon -- 106053 | |
| dc.description.abstract | Medical 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.doi | 10.1109/SIU.2014.6830352 | |
| dc.identifier.endpage | 809 | |
| dc.identifier.isbn | 978-147994874-1 | |
| dc.identifier.scopus | 2-s2.0-84903776758 | |
| dc.identifier.scopusquality | N/A | |
| dc.identifier.startpage | 806 | |
| dc.identifier.uri | https://doi.org/10.1109/SIU.2014.6830352 | |
| dc.identifier.uri | https://hdl.handle.net/11508/41231 | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | tr | |
| dc.publisher | IEEE Computer Society | |
| dc.relation.ispartof | 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings | |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_Scopus_20260511 | |
| dc.subject | Artificial 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.title | Abdominal image segmentation on Android based mobile devices | |
| dc.title.alternative | Android işletim sistemli mobil cihazlarda abdominal görüntü bölütleme | |
| dc.type | Conference Object |







