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Reseach Article

Segmentation of Lung Lobes and Fissures for Surgical Pre Planning

by S. N. Kumar, M. Marsaline Beno
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 51 - Number 9
Year of Publication: 2012
Authors: S. N. Kumar, M. Marsaline Beno
10.5120/8068-1461

S. N. Kumar, M. Marsaline Beno . Segmentation of Lung Lobes and Fissures for Surgical Pre Planning. International Journal of Computer Applications. 51, 9 ( August 2012), 12-16. DOI=10.5120/8068-1461

@article{ 10.5120/8068-1461,
author = { S. N. Kumar, M. Marsaline Beno },
title = { Segmentation of Lung Lobes and Fissures for Surgical Pre Planning },
journal = { International Journal of Computer Applications },
issue_date = { August 2012 },
volume = { 51 },
number = { 9 },
month = { August },
year = { 2012 },
issn = { 0975-8887 },
pages = { 12-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume51/number9/8068-1461/ },
doi = { 10.5120/8068-1461 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:49:55.974673+05:30
%A S. N. Kumar
%A M. Marsaline Beno
%T Segmentation of Lung Lobes and Fissures for Surgical Pre Planning
%J International Journal of Computer Applications
%@ 0975-8887
%V 51
%N 9
%P 12-16
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Medical imaging is the technique that is used to create images of the human body or parts for clinical purposes (medical procedures seeking to reveal diagnose or examine disease). The CT images provide detailed information of anatomy of lungs, which could be used for better surgical planning of treating Lung Cancer This Work, proposes a method for Segmentation of Lung lobes and fissures for surgical planning of treating Lung Cancer. This work presents a 'lobe and fissure' segmentation algorithm that uses a two stage approach. This work presents a threshold based lobe segmentation algorithm. Modified adaptive fissure sweeping and Wavelet Transform are used to segment Lung fissures in CT images. The unseen or partially seen fissures are enhanced and segmented. The main modules of this work are Preprocessing, Lung Segmentation by Iterative Threshold method, Fissure Region Sweeping, Wavelet Transform, Otsu's binarization, Fissure verification, Interpolation and Extension of Fissures. In the Preprocessing work noises are reduced. The preprocessing is done by fuzzy filter. In the next module lung area are segmented by Iterative Threshold Method. Then the fissure regions are collected. Next Wavelet Transform generates the features. Then Otsu's method is adopted for binarization. Next Interpolation is done and fissure is extended up to needed length. Finally Fissure information are extracted and displayed.

References
  1. . B. N. Raasch, E. W. Carsky, E. J. Lane, J. P. O'Callaghan, and E. R. Heitzman, "Radiographic anatomy of the interlobar fissures: A study of 100 specimens," Amer. J . Roentgenol. , vol. 138, pp. 647–554, 1982
  2. M. Kass, A. Witkin, and D. Terzopoulos, "Snakes:Active contour models,"Int. J. Comput. Vis. , vol. v1, pp. 321–331, 1987.
  3. . R. M. Haralick, S. R. Stenberg, and X. Zhuang, "Image analysis using mathematical morphology," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 9, no. 4, pp. 532–550, Jul. 1987
  4. . M. Kubo, N. Niki, S. Nakagawa, K. Eguchi, M. Kaneko, N. Moriyama,H. Omatsu, R. Kakinuma, and N. Yamaguchi, "Extraction algorithm of pulmonary fissures from thin-section CT images based on linear feature detector method," IEEE Trans. Nucl. Sci. , vol. 46, no. 6, pp. 2128–2133, Dec. 1999
  5. . M. Kubo, Y. Kawata, N. Niki, K. Eguchi, H. Ohmatsu, R. Kakinuma, M. Kaneko, M. Kusumoto, N. Moriyama, K. Mori, and H. Nishiyama, "Automatic extraction of pulmonary fissures from multidetector-row CT images," in Proc. IEEE Int. Conf. Imag. Process. (ICIP), pp. 1091–1094, 2001
  6. . J. -M. Kuhnigk, H. Hahn, M. Hindennach, V. Dicken, S. Krass, and H. -O. Peitgen, "Lung lobe segmentation by anatomy-guided 3-D watershed transform," Proc. SPIE (Med. Imag. ), vol. 5032, pp. 1482–1490,2003.
  7. . Takahiro Ohkawal, Syoji Kobashi', Katsuya Kondo', Yutaka Hatal, Tonioham Nakaiio',"Tubular Tissue-Based Segmentation Of Lung Lobes From Chest Mdct Images", Cancer and Thoracic Surgery, Graduate School of Medicine, Okayama University, 2003.
  8. . Yoshinori itai,seji ishikawa,"Automatic segmentation of lung areas based on snakes and extraction of abnormal areas", 2005
  9. . . L. Zhang, E. A. Hoffman, and J. M. Reinhardt, "Atlas-driven lung lobe segmentation in volumetric X-ray CT images," IEEE Trans. Med. Imag. , vol. 25, no. 1, pp. 1–16, Jan. 2006.
  10. . J. Wang, M. Betke, and J. P. Ko, "Pulmonary fissure segmentation on CT,"Med. Imag. Anal. , vol. 10, pp. 530–547, 2006.
  11. . American Cancer Society, Cancer Facts and Figures 2008. Atlanta, GA: American Cancer Society, 2008.
  12. . Jiantao Pu, Bin Zheng, Joseph K. Leader, Carl Fuhrman, Friedrich Knollmann, Amy Klym, and David Gur,"Pulmonary Lobe Segmentation in CT Examinations Using Implicit Surface Fitting"',IEEE transactions on medical imaging, vol. 28, no. 12, december 2009.
  13. . Soumik Ukil,Joseph M Reinhardt,"Anatomy Guided Lung Lobe Segmentation In X-Ray Ct Images",Ieee Transactions On Medical Imaging,Vol 28,No2 Feburary 2009.
  14. . z. Faizal khan,S. N Kumar,V. Kavitha," Efficient Algorithm to Enhance Lung Lobe Images using FuzzyFiltering",International Journal of Computer Applications(0975 – 8887) Volume 25– No. 6, July 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Segmentation human lungs Otsu's Method