You are in:Home/Publications/Anter AM, Hassanien AE, Abu ElSoud M, Azar AT (2015) Automatic Liver Parenchyma Segmentation System from Abdominal CT Scans using Hybrid Techniques. Int. J. Biomedical Engineering and Technology, 17(2): 148-168

Dr. Assoc. Prof. Ahmad Taher Azar :: Publications:

Title:
Anter AM, Hassanien AE, Abu ElSoud M, Azar AT (2015) Automatic Liver Parenchyma Segmentation System from Abdominal CT Scans using Hybrid Techniques. Int. J. Biomedical Engineering and Technology, 17(2): 148-168
Authors: Not Available
Year: 2015
Keywords: Not Available
Journal: Not Available
Volume: Not Available
Issue: Not Available
Pages: Not Available
Publisher: Not Available
Local/International: International
Paper Link: Not Available
Full paper Not Available
Supplementary materials Not Available
Abstract:

In this paper, a multi-layer heuristic approach is introduced to segment liver region from other tissues in multi-slice CT images. Image noise is a principal factor which hampers the visual quality of medical images and can therefore lead to misdiagnosis. To address this issue, we first utilise an algorithm based on median filter to remove noise and enhance the contrast of the CT image. This is followed by performing an adaptive threshold algorithm and morphological operators to preserve the liver structure and remove the fragments of other organs. Then, connected component labelling algorithm was applied to remove false positive regions and focused on liver region. To evaluate the performance of the proposed system, we present tests on different liver CT scans images. The experimental results show that the overall accuracy offered by the employed system is high compared with other related works as well as very fast which segment liver from abdominal CT in less than 0.6 s/slice.

Google ScholarAcdemia.eduResearch GateLinkedinFacebookTwitterGoogle PlusYoutubeWordpressInstagramMendeleyZoteroEvernoteORCIDScopus