Browse > Article
http://dx.doi.org/10.9708/jksci.2012.17.3.051

Hepatic Vessel Segmentation using Edge Detection  

Seo, Jeong-Joo (Dept. of Information Communications Engineering, Chungnam National University)
Park, Jong-Won (Dept. of Information Communications Engineering, Chungnam National University)
Abstract
Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.
Keywords
Automatic segmentation of hepatic vessel; MDCT image processing; Edge detection; error correction on horizontal and vertical direction;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Jonathan B. Kruskal and Robert A. Kane, "Intraoperative US of the Liver: Techniques and Clinical Applications," RadioGraphices, vol.26, No.4, pp.1067-1084, 2006.   DOI   ScienceOn
2 Will Schroeder, Den Martin, Bill Lorensen, The Visualization Toolkit An Object-Oriented Approach To 3D Graphics, Third Edition, Kitware Inc., USA.
3 A. Radtke, G. C. Sotiropoulos, S. Nadalin, E. P. Molmenti, T. Schroeder, and et al., "Preoperative Volume Prediction in Adult Live Donor Liver Transplantation: 3-D CT Volumetry Approach to Prevent Miscalculations," Eur J Med Res, vol.13, pp.319-326, July 2008.
4 Fulcher AS, Szucs RA, Bassignani MJ, and Marcos A, "Right lobe living donor liver transplantation: preoperative evaluation of the donor with MR imaging," AJR Am J Roentgenol, Vol.176, pp.1483-1491, 2001.   DOI   ScienceOn
5 Michael J. Guiney, Jonathan B. Kruskal, Jacob Sosna, and et al., "Multi-Detector Row CT of Relevant Vascular Anatomy of the Surgical Plane in Split-Liver Transplantation," Radiology, Vol.229, No.2, pp.401-407, Nov. 2003.   DOI   ScienceOn
6 B. D. Thackray and A. C. Nelson, "Semiautomatic segmentation of vascular network images using a rotating structuring element(ROSE) with mathematical morphology and dual feature thresholding," IEEE Trans. on Medical Imaging, Vol.12. No.3, pp.385-392, Sept. 1993.   DOI   ScienceOn
7 Adams R. and Bischof L., "Seeded region growing," IEEE Trans Pattern Anal Mach Intell, Vo.16, pp.641-647, 1994.   DOI   ScienceOn
8 Jeongjoo Seo, Gangmin Ryu, Yang Fei, and Jongwon Park, "Segmentation of Liver on MDCT Image," Proceedings of KISS Korea Computer Congress 2005, Vol.32, No.1(B), pp.802-804, 2005.
9 Canny, J., "A Computational Approach to Edge Detector", IEEE Transactions on PAMI, pp. 679-698, 1986.
10 Mohamed Roushdy, "Comparative Study of Edge Detection Algorithms Applying on the Grayscale Noisy Image Using Morphological Filter," GVIP Journal, Vol.6, Issue 4, pp.17-23, December 2006.
11 Michelle Doherty, Nicole Bordes, Thomas Hugh, and Bernard Pailthorpe, "3D Visualisation of Tumours and Blood Vessels in Human Liver," VIP2002, Vol. 22, pp.27-31, 2003.