• DocumentCode
    152463
  • Title

    Abdominal image segmentation on Android based mobile devices

  • Author

    Tuncer, Seda Arslan ; Alkan, Ali

  • Author_Institution
    Enformatik Bolumu, Firat Univ., Elazig, Turkey
  • fYear
    2014
  • fDate
    23-25 April 2014
  • Firstpage
    806
  • Lastpage
    809
  • 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.
  • Keywords
    biological tissues; computerised tomography; image recognition; image segmentation; liver; medical image processing; patient diagnosis; smart phones; Android based mobile devices; Zijdenbos similarity index; abdominal image segmentation; computed tomography images; decision support system study; diagnostic lesions; health services; information technology; lesion liver detection; liver segmentation; manual segmentation; medical experts; medical services; mobile environment; organ tissues; radiologists; segmentation procedure; technological infrastructure developments; Androids; Computed tomography; Conferences; Humanoid robots; Image segmentation; Liver; Signal processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2014 22nd
  • Conference_Location
    Trabzon
  • Type

    conf

  • DOI
    10.1109/SIU.2014.6830352
  • Filename
    6830352