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Reseach Article

Automated Segmentation of Angio Vessels

Published on July 2012 by S. Sathish Kumar, R. Amutha
Advanced Computing and Communication Technologies for HPC Applications
Foundation of Computer Science USA
ACCTHPCA - Number 4
July 2012
Authors: S. Sathish Kumar, R. Amutha
8270fb88-bf19-4508-b380-67599dfc3da6

S. Sathish Kumar, R. Amutha . Automated Segmentation of Angio Vessels. Advanced Computing and Communication Technologies for HPC Applications. ACCTHPCA, 4 (July 2012), 33-40.

@article{
author = { S. Sathish Kumar, R. Amutha },
title = { Automated Segmentation of Angio Vessels },
journal = { Advanced Computing and Communication Technologies for HPC Applications },
issue_date = { July 2012 },
volume = { ACCTHPCA },
number = { 4 },
month = { July },
year = { 2012 },
issn = 0975-8887,
pages = { 33-40 },
numpages = 8,
url = { /specialissues/accthpca/number4/7577-1031/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Advanced Computing and Communication Technologies for HPC Applications
%A S. Sathish Kumar
%A R. Amutha
%T Automated Segmentation of Angio Vessels
%J Advanced Computing and Communication Technologies for HPC Applications
%@ 0975-8887
%V ACCTHPCA
%N 4
%P 33-40
%D 2012
%I International Journal of Computer Applications
Abstract

Segmentation is one of the major steps in the analysis of medical images, as it outputs the attributes extracted from the input images. The need for automated width detection lies in analyzing the presence or absence of specific anomalies. The paper presents the segmentation of the Coronary artery tree from the angiographic images. This is done by extracting or segmenting the vessels and thereby detecting its width. The proposed algorithm consists of two main steps, namely the pre-processing and the segmentation. In the pre-processing step, the Hessian matrix analysis is done to track the coronary vessel structures from the original image and the Frangi 2D filter is used to enhance the angiogram image. In the second step, the segmentation is done by morphing the filtered image and finally the width of the segmented blood vessel in the coronary angiogram image is determined. Also various parameters such as the Total Vessel Length (TVL), Total Input Image Area (TIIA), Segmented Image Area (SIA) and Vessel Image Percent (VIP), Sensitivity, Specificity, and the computational time are calculated for the performance evaluation and are compared with the existing methods. The results prove that the proposed method is very efficient than the existing methods.

References
  1. Albert C. S. Chung, "Image Segmentation Methods for detecting blood vessels in Angiography", in IEEE proceedings 2006.
  2. Ana Maria Mendonca, Aurelio Campilho, " Segmentation of Retinal Blood vessels by combining the detection of centerlines and Morphological reconstruction", in IEEE transactions on Medical Imaging , Vol. 25, No. 9, September 2006.
  3. Chih-Yang Lin, Yu-Tai Ching, " Extraction of Coronary Arterial Tree using Cine X-ray Angiograms", in International Journal of Biomedical Engineering-Applications, basis and communications, pp 111 – 120, Vol. 17, 3 June 2005.
  4. Chris McIntosh and Ghassan Hamarneh, "Vessel Crawlers: 3D Physically-based Deformable Organisms for Vasculature Segmentation and Analysis", in IEEE proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06), 2006.
  5. C. Kirbas and F. Quek, "A review of vessel extraction techniques and alogorithms, ACM Computing Surveys", Vol. 36 (2), pp 81-121, 2004
  6. Eiho. S and Qian. Y, "Detection of Coronary artery tree using morphological operator", Computers in Cardiology, pp 525-528, 1997.
  7. Farsad Zamani Boroujeni, Rahmita Wirza, Oteh Maskon, Alireza, Majid Khalilian, " An Improved Seed Point Detection Algorithm for Centreline Tracing in Coronary Angiograms", in IEEE International Conference on Information Technology, pp 352 – 357, 2010.
  8. J. Brieva, P. Ponce, "Evaluation of Segmentation Algorithms for Coronary Angiography", in IEEE International conference, pp 5555-5558, 2007.
  9. Kostas Haris, Serafim N. Efstratiadis, Nicos Maglaveras, Costas Pappas, "Model-based Morphological Segmentation and Labelling of Coronary Angiograms", in IEEE transactions on Medical Imaging, Vol. 18, No. 10, October 1999.
  10. Lee J. S. J. ,Haralick R. M. ,and Shapiro L. G. , "Morphology edge detection", IEEE proceedings,vol. 3, pp 142-156,1987.
  11. Lizhe Xie, Yining Hu, Yang Chen, Limin Luo, " Maximum A Posteriori based Coronary angiograms segmentation method with Vessel-like feature and Markov random field", in IEEE International Conference of Medical Image Analysis and Clinical Application (MIACA), pp 123-126,2010.
  12. Marcin Rudzki, " Vessel detection method based on the Eigenvalues of the Hessian Matrix and its Applicability to Airway Tree Segmentation", in XI International PhD Workshop OWD 2009, pp 100-105, 17-20 October 2009.
  13. Masoomeh Ashoorirad, Rasool Baghbani, " Blood Vessel Segmentation in Angiograms using Fuzzy Interference system and Mathematical Morphology" , in IEEE International conference on Signal Processing Systems (ICSPS'09) , pp 272-276, 2009.
  14. M. J Rastegar Fatemi, Seyed Mostafa Mirhassani and Bardia Yousefi, " Vessel Segmentation in X-ray Angiographic Images using Hessian Based Vesselness Fliter and Wavlet based Image Fusion", in IEEE International Conference, July 2010.
  15. Pascal Fallavollita and Farida Cheriet, "Towards an Automatic Coronary Artery Segmentation Algorithm", in IEEE EMBS Annual International Conference, New York City, USA, Aug 30 – Sept 3, 2006.
  16. Rivest Jean, "Morphological Operators on Complex Signal", signal processing, vol. 84, pp 133-139, 2004.
  17. Ruan lakemond, Clinton Fookes, Sridha Sridharan, " Affine Adaptation of local Image Features using the Hessian Matrix", in Advanced Video and Signal Based Surveillance, IEEE Computer Society, pp 496-501 ,2009.
  18. Rubiel Vargas and Panos Liatsis, " Vessel Extraction in Fluoresecein Angiograms of the Human Retina using a Supervised Classifier", in IEEE Development in E-systems Engineering, pp 23 – 28, 2010.
  19. Shoujun Zhou, Wufan Chen, Zhengbo Zhang and Jian Yang, "Automatic Segmentation of Coronary Angiograms Based on Probabilistic Tracking ", in Proceedings of IEEE, 2009.
  20. Wenwei Kang, Ke Wang and Qingzhu Wang, "Segmentation Method based on Transition Region Extraction for Coronary Angiograms", in IEEE proceedings of the 2009 IEEE International Conference on Mechactronics and Automation, August 9-12, Changchun, China,2009.
  21. Wenwei Kang, Ke Wang, Wanzhong Chen, Wenying Kang,"Segmentation Method based on Fusion Algorithm for Coronary Angiograms", in IEEE proceedings, 2009.
  22. Wenwei Kang, Ke Wang, Wanzhong Chen, Yong Li, " Segmentation of Coronary Arteries Based on Transition Region Extraction", in IEEE International Asia Conference on Infromation in Control, Automation and Robotics, pp 333- 336, 2010.
  23. Yan Yang, Allen Tannenbaum, Don Giddens, " Knowledge. based 3D Segmentation and reconstruction of Coronary Arteries using CT images", in IEEE proceedings of the 26th Annual International Conference of the IEEE EMBS, San Francisco, CA, USA, September 1-5, 2004.
  24. Y. H. Yu, "Study of Coronary artery Segmentation from Coronary digital angiography", Shandong Journal of Biomedical Engineering, Vol. 21, pp 5-10, 2002.
  25. Z. W. Tang, H. Zhang, and G. S. Hu, "Morphological multiscale vessel enhancement for coronary angiograms", J Tsinghua Univ (Sci&Tech), Vol. 46, No. 3, pp 418-420, 2006.
  26. Zulong Yu and Kaiqiong Sun, " Vessel Segmentation on Angiogram using Morphology Driven Deformable Model", in IEEE International Conference on Biomedical Engineering and Informatics (BMEI 2010), pp 675 – 678, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Angiographic Image Gabor Filter Hessian Matrix Image Enhancement Frangi 2d Filter Morphology Segmentation Width Detection