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An Optimized Technique of Tree Generation for Artery/Vein Separation in Non-Contrast CT Imaging

by Arya Varghese, J. Ramya
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 18
Year of Publication: 2013
Authors: Arya Varghese, J. Ramya
10.5120/12640-8989

Arya Varghese, J. Ramya . An Optimized Technique of Tree Generation for Artery/Vein Separation in Non-Contrast CT Imaging. International Journal of Computer Applications. 72, 18 ( June 2013), 5-10. DOI=10.5120/12640-8989

@article{ 10.5120/12640-8989,
author = { Arya Varghese, J. Ramya },
title = { An Optimized Technique of Tree Generation for Artery/Vein Separation in Non-Contrast CT Imaging },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 18 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 5-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number18/12640-8989/ },
doi = { 10.5120/12640-8989 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:38:14.380095+05:30
%A Arya Varghese
%A J. Ramya
%T An Optimized Technique of Tree Generation for Artery/Vein Separation in Non-Contrast CT Imaging
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 18
%P 5-10
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Arterial and venous trees separation in non-contrast pulmonary CT imaging facilitates extraction of quantitative measures at different tree levels. Reconstruction and separation of arterial and venous vascular trees is an essential step for diagnostic application systems used for maladies such as pulmonary embolism and coronary artery disease[1]. Although, higher tree generations of vasculature, arteries and veins are indistinguishable by their intensity values, automatic artery-vein (AV) reconstruction and separation still remains a challenging problem in computational imaging and geometry processing due to patient specific structural abnormalities of vascular trees. This paper presents a novel technique of multi-scale fuzzy enhanced topo-morphologic opening algorithm (MSFTMO) to separate artery and vein from non-contrast CT images, which can be used for diagnosing arteriosclerosis as well. The algorithm combines fuzzy distance transform, a morphologic feature, with a topologic connectivity and a new morphological reconstruction step to iteratively open multi-scale fusions starting at large scales, progressing towards smaller scales[1][2]. The algorithm is applied on fuzzy segmentation results via a small amount of intuitive interactions using an efficient graphical user interface.

References
  1. Saha P. K, Gao Z, Alford S. K, Sonka M and Hoffman E. A, "Topomorphologic separation of fused isointensity objects via multiscale opening: separating arteries and veins in 3-D pulmonary CT," IEEE Trans Med Imag,. 840–851, vol. 29, pp, 2010.
  2. Zhiyun Gao, Randall W. Grout, Colin Holtze, Eric A. Hoffman, and Punam K. Saha_, "A new paradigram of interactive Artery/Vein separation in non-contrast pulmonary CT imaging using multi-Scale topomorphologic opening," IEEE Journ Med Imag 2012.
  3. G. Y. El-Khoury, M. H. Kathol, and W. W. Daniel, "Imaging of acute injuries of the cervical spine: Value of plain radiography, CT, and MR imaging," AJR Amer. J. Roentgenol. , vol. 164, pp. 43–50, 1995.
  4. H. Shikata, E. A. Hoffman, and M. Sonka, "Automated segmentationof pulmonary vascular tree from 3D CT images," in Proc. SPIE Int. Symp. Med. Imag. , San Diego, CA, 2004, pp. 107–116.
  5. Z. H. Cho, J. P. Jones, and M. Singh, Foundation of Medical Imaging. New York: Wiley, 1993.
  6. X. Liu, D. Z. Chen, M. Tawhai, E. Hoffman, and M. Sonka, "Measurement,evaluation and analysis of wall thickness of 3D airway treesacross bifurcations," in Proc. 2nd Int. Workshop Pulm. Image Process. , London, UK, 2009, pp. 161–171.
  7. J. K. Udupa and G. T. Herman, "3D Imaging in Medicine". Boca Raton,FL: CRC Press, 1991.
  8. K. C. Ciesielski, J. K. Udupa, P. K. Saha, and Y. Zhuge, "Iterative relative fuzzy connectedness for multiple objects with multiple seeds," Comput. Vis. Image Understand. , vol. 107, pp. 160–182, 2007.
  9. P. K. Saha and J. K. Udupa, "Relative fuzzy, P. K. Saha, and D. Odhner, "Artery-vein separation via MRA - an image processing approach," IEEE Trans Med Imag, vol. 20, pp. 689–703, 2001.
  10. J. K. Udupa and P. K. Saha, "Fuzzy connectedness in image segmentation," in Proc. IEEE, Emerging Med. Imag. Technol. ,, 2003, vol. 91,pp. 1649–1669.
  11. T. Yonekura, "Classification algorithm of pulmonary vein and artery based on multi-slice CT image," in Proc. SPIE: Med. Imag. , San Diego, CA, vol. 6514, pp. 65 142E1–65 142E8 2007.
  12. Saha P. K and Udupa J. K, "Iterative relative fuzzy connectedness and object definition: theory, algorithms and applications in image segmentation," in Proc of IEEE MMBIA 2000.
  13. T. Lei, J. K. Udupa segmentation," in Proc. IEEE Workshop Math. Methods Biomed. Image Anal. , Hilton Head, , pp. 28–35, SC, 2000.
  14. P. K. Saha and B. B. Chaudhuri, "3D digital topology under binary transformation with applications," Comput. Vis. Image Understand. ,vol. 63, pp. 418–429, 1996.
  15. C. M. van Bemmel, L. J. Spreeuwers, M. A. Viergever, and W. J. Niessen, "Level-set-based artery-vein separation in blood pool agent CE-MR angiograms," IEEE Trans. Med. Imag. , vol. 22, no. 10, pp. 1224–1234, Oct. 2003.
  16. A. L. D. Beckers and A. W. M. Smeulders, "Optimization of length measurements for isotropic distance transformations in three dimension," CVGIP: Image Understand. , vol. 55, pp. 296–306, 1991.
  17. P. K. Saha and J. K. Udupa, "Iterative relative fuzzy connectedness and object definition: Theory, algorithms, and applications in image connectedness among multiple objects: Theory, algorithms, and applications in image segmentation," Comput. Vis. Image Understand. , vol. 82, pp. 42–56, 2001.
  18. J. K. Udupa, P. K. Saha, and R. A. Lotufo, "Relative fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 24, no. 11, pp. 1485–1500, Nov. 2002.
  19. J. K. Udupa and S. Samarasekera, "Fuzzy connectedness and object definition: Theory, algorithms, and applications in image segmentation," Graph. Models Image Process. , vol. 58, pp. 246–261, 1996.
  20. LaMuraglia, G. M. ; Harvard Med. Sch. , Massachusetts Gen. Hospital, Boston, MA, USA ; Prince, M. R. ; Nishioka, N. S. ; Obremski, S. ,Optical properties of human arterial thrombus, vascular grafts, and sutures: implications for selective laser thrombus ablation,Quantum Electronics, IEEE Journal of (Volume:26 ,Issue: 12 ).
  21. Chun Xu ; Dept. of Mech. Eng. & Mech. , Drexel Univ. , Philadelphia, PA, USA ; Wootton, D. ,"A model of platelet concentration sampling in arterial flow" (Volume:2, 2007).
  22. D. Pate, D. Resnick, M. Andre, D. J. Sartoris, S. Kursunoglu, D. Bielecki, P. Dev, and A. Vassiliadis, "Perspective: Three-dimensional imaging of the musculoskeletal system," AJR Amer. J. Roentgenol. , vol. 147, pp. 545–551, 1986.
  23. A. K. Jain,"Fundamentals of Digital Image Processing". Upper Saddle River, NJ: Prentice Hall, 1989.
  24. T. Buelow, R. Wiemker, T. Blaffert, C. Lorenz, and S. Renisch, "Automatic extraction of the pulmonary artery tree from multi-slice CT data," vol. 5746, pp, in Proc. SPIE: Med. Imag. , San Diego, CA, 2005.
  25. T. Yonekura, "Classification algorithm of pulmonary vein and artery based on multi-slice CT image," in Proc. SPIE: Med. Imag. , San Diego,CA, 2007, vol. 6514, pp. 65 142E1–65 142E8.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy segmentation Fuzzy connectivity Local Update and user interface multi-scale fuzzy enhanced topo-morphologic opening algorithm arteriosclerosis

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