Liver Segmentation from Abdominal CT Volumes Based on Graph Cuts and Border Marching

LIAO Miao; ZHAO Yuqian; ZENG Yezhan; HUANG Zhongchao; ZOU Beiji

doi:10.11999/JEIT151005

Volume 38 Issue 6

Jun. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(6): 1552-1556

LIAO Miao, ZHAO Yuqian, ZENG Yezhan, HUANG Zhongchao, ZOU Beiji. Liver Segmentation from Abdominal CT Volumes Based on Graph Cuts and Border Marching[J]. Journal of Electronics & Information Technology, 2016, 38(6): 1552-1556. doi: 10.11999/JEIT151005

Citation:

LIAO Miao, ZHAO Yuqian, ZENG Yezhan, HUANG Zhongchao, ZOU Beiji. Liver Segmentation from Abdominal CT Volumes Based on Graph Cuts and Border Marching[J]. Journal of Electronics & Information Technology, 2016, 38(6): 1552-1556. doi: 10.11999/JEIT151005

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Liver Segmentation from Abdominal CT Volumes Based on Graph Cuts and Border Marching

doi: 10.11999/JEIT151005

1.
(School of Geosciences and Info-Physics, Central South University, Changsha 410083, China)
2.

Funds:

The National Natural Science Foundation of China (61172184, 61379107, 61402539, 61174210), Program for New Century Excellent Talents in University of Ministry of Education in China (NCET-13-0603), Specialized Research Fund for the Doctoral Program of Higher Education in China (20130162110016), Program for Hunan Province Science and Technology Basic Construction (Grant 20131199), Hunan Provincial Science and Technology Project of China (2015RS4008), Fundamental Research Funds for the Central Universities of Central South University (2014ZZTS053), Hunan Provincial Innovation Foundation for Postgraduate (CX2014B052)

Received Date: 2015-09-08
Rev Recd Date: 2016-01-22
Publish Date: 2016-06-19

Abstract

Abstract

A novel method for liver segmentation from abdominal CT volumes based on graph cuts and border marching is proposed. First, to exclude complex background and highlight liver region, liver intensity and appearance models are built according to the characteristics of a given CT volume. Then, the intensity and appearance models together with location information from neighbor segmented slice are effectively integrated into graph cuts cost computation to segment the CT volume initially and automatically. Finally, to solve the under-segmentation issue of liver vessel, a boundary compensation method based on border marching is proposed. The proposed method is tested and compared with some other methods on 30 CT volumes from XHCSU14 and SLIVER07 databases. The experimental results show that the proposed method can segment livers integrally and effectively from abdominal CT volumes, with higher accuracy and robustness.
- Medical image segmentation,
- Graph cuts,
- Border marching,
- Gaussian fitting,
- Principal Components Analysis (PCA)

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References(13)

References

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