The week's pick
Reseach Article
An Improved Retinal Blood Vessel Segmentation Algorithm based on Multistructure Elements Morphology
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 57 - Number 16 |
| Year of Publication: 2012 |
| Authors: Sifna N. Shajahan, Rajesh Cherian Roy |
10.5120/9200-3730
|
Sifna N. Shajahan, Rajesh Cherian Roy . An Improved Retinal Blood Vessel Segmentation Algorithm based on Multistructure Elements Morphology. International Journal of Computer Applications. 57, 16 ( November 2012), 31-36. DOI=10.5120/9200-3730
Abstract
Retina is the portion where many important eye diseases and systemic diseases manifest. By evaluating the retinal blood vessels, doctors can diagnose the primary stages of diabetic retinopathy, age related macular degeneration, glaucoma etc which may eventually lead to blindness. The objective is to develop an algorithm that segments the retinal blood vessels in a short time and with high accuracy. But the low gray level contrast and dynamic range of the image make the blood vessel segmentation process very difficult. A new multiscale transform, Curvelet transform, is used for retinal image contrast enhancement. Since the blood vessels are distributed in various directions multistructure elements morphology is used to find the blood vessel edges. The false edges are removed by morphological reconstruction. A locally applied level dependent thresholding algorithm with connected component analysis and length filtering removes the remaining false edges after reconstruction step. The proposed algorithm, when experimentally applied on images from the DRIVE database, gave an accuracy of more than 97% in less than 15 s, thus showing its effectiveness in retinal blood vessel segmentation.
References
- S. Chaudhuri, S. Chatterjee, N Katz, M Nelson and M Goldbaum "Detection of blood vessel in retinal images using two-dimensional matched filters," IEEE Trans. Med. Imag. ,vol 8, no. 3, pp 263-269,Sep. 1989
- Soares, Joao VB, Jorge JG Leandro, Roberto M. Cesar, Herbert F. Jelinek, and Michael J. Cree, "Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification," IEEE Trans Medical Imag. , vol. 25, no. 9 , May 2006.
- J. J. Staal, M. D. Abramoff, M. Niemeijer, M. A. Viergever, and B. van Ginneken, "Ridge based vessel segmentation in color images of the retina," IEEE Trans. Med. Imag. , vol. 23, no. 4, pp. 501–509, Apr. 2004.
- Mohammad Saleh Miri and Ali Mahloojifar, "Retinal image analysis using curvelet transform and multistructure elements morphology by reconstruction," IEEE Trans. Biomed. Imag. , vol58,no. 5, pp1183-1191,may 2011
- Peng Feng, Yingjun Pan , Biao Wei, Wei Jin, Deling Mi, "Enhancing retinal image by the Contourlet transform," Pattern Recognition Letters, vol. 28, 516–522, 2007
- E. J. Candes and D. L. Donoho, "Curvelets—A surprisingly effective nonadaptive representation for objects with edges," in Curves and Surfaces, Nashville, TN: Vanderbilt Univ. Press, 1999, pp. 123–143.
- E. Candes, L. Demanet, D. Donoho, and L. Ying, "Fast discrete curvelet transforms," Multiscale Model. Simul. , vol. 5, no. 3, pp. 861–899, 2006
- Y. Zhao, W. Gui, and Zh. Chen, "Edge detection based on multi-structure elements morphology," Proc. 6th World Congr. Intell. Control Autom. , pp. 9795–9798, 2006.
- S. Mukhoopadhyay and B. Chanda, "Multiscale morphological segmentation of gray-scale images," IEEE Trans. Image Process. , vol. 12, no. 5, pp. 533–549, May 2003.
- N. Otsu, "A threshold selection method from gray level histograms," IEEE Trans. Syst. , Man, Cybern. , vol. SMCA-9, no. 1, pp. 62–66, Jan. 1979.
- J. Starck, F. Murtagh, E. J. Candes, and D. L. Donoho, "Gray and color image contrast enhancement by the curvelet transform," IEEE Trans. Image Process. , vol. 12, no. 6, pp. 706–717, Jun. 2003.
- Y. Ma,M. Yang, and L. Li, "A kind of omni-directional multi-angle structuring elements adaptive morphological filters," J. Chin. Inst. Commun. , vol. 25, no. 9, pp. 86–92, 2004.
- A. M. Mendonca and A. Campilho, "Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction," IEEE Trans. Med. Imag. , vol. 25, no. 9, pp. 1200–1213, Sep. 2006.
- Rajkumar K. K. and G. Raju "Enhancement of Mammograms Using Tophat Filtering and Wavelet Decomposition," Journal of Computer & Mathematical Sciences, Vol. 2 , no. 6, pp. 812-818 , December 2011
- Waltz, Frederick M. , and John WV Miller. "Comparison of connected-component algorithms. " Proceedings of SPIE- The International Society for Optical Engineering. Vol. 3836. 1999.
- S. Supot, Ch. Thanapong, P. Chuchart, and S. Manas, "Automatic segmentation of blood vessels in retinal image based on fuzzy k-median clustering," in Proc. IEEE Int. Conf. Integr. Technol. ,Mar. 2007, pp. 584–588.
- E. Ardizzone, R. Pirrone, O. Gambino, and S. Radosta, "Blood vessels and feature points detection on retinal images," in Proc. 30th Annu. Int. IEEE EMBS Conf. , Aug. 2008, pp. 2246–2249
- M. E. Martinez-Perez, A. D. Hughes, S. A. Thom, A. A. Bharath, and K. H. Parker, "Segmentation of blood vessels from red-free and fluorescein retinal images," Med. Image Anal. , vol. 11, pp. 47–61, 2007.
Index Terms
Keywords