Title: Automatic liver parenchyma segmentation system from abdominal CT scans using hybrid techniques

Authors: Ahmed M. Anter; Aboul Ella Hassanien; Mohamed Abu ElSoud; Ahmad Taher Azar

Addresses: Faculty of Computers and Information, CS Department, Mansoura University, Mansoura City, Egypt; Scientific Research Group in Egypt (SRGE), Egypt ' Faculty of Computer and Information, Beni Suef University, Beni Suef, Egypt; Scientific Research Group in Egypt (SRGE), Egypt ' Faculty of Computers and Information, CS Department, Mansoura University, Mansoura City, Egypt ' Faculty of Computers and Information, Benha University, Benha, Egypt

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.

Keywords: DICOM; CT images; adaptive threshold; CAD; CCL; ROI; morphology; liver parenchyma segmentation; abdominal scans; CT scans; computed tomography; image quality; medical images; median filter; liver scans; image segmentation.

DOI: 10.1504/IJBET.2015.068052

International Journal of Biomedical Engineering and Technology, 2015 Vol.17 No.2, pp.148 - 167

Received: 09 Aug 2014
Accepted: 14 Oct 2014
Published online: 15 Mar 2015 *

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