A High Performance Hybrid Technique of Microaneurysm Extraction Using Vessel Suppression and Connected Component Extraction
(*) Corresponding author
Detection of microaneurysms in the early stage is a crucial step towards identifying non - proliferative diabetic retinopathy in diabetic patients. Micro aneurysms appear in the form of tiny red dots in fundus images near the blood vessels. Thus making it is very difficult to identify them through ordinary techniques. In this paper we propose a hybrid technique which uses vessel suppression in increase the performance and accuracy of microaneurysms detection. The entire process can be divided into four stages. First the pre-processing stage which enhances the contrast and eliminates noise by contrast limited histogram equalization and bilateral filter respectively. Then multiscale hessian transform based enhancement is performed which includes vessel extraction and suppression. Finally the microaneurysms are extracted using connect component extraction and classified based on features extracted. This technique eliminates the number of false positives detected at every stage thus improving the sensitivity of the system. The algorithm has been thoroughly tested on numerous images and it outperformed the existing counterparts.
Copyright © 2015 Praise Worthy Prize - All rights reserved.
Istvan Lazar and Andras Hajdu, Retinal Microaneurysm Detection Through Local Rotating Cross-Section Profile Analysis, IEEE Transactions on Medical Imaging, Vol. 32, No. 2, February 2013.
Sandip Pradhan, S. Balasubramanian, V. Chandrasekaran and Sri Sathya Sai University, An Integrated Approach using Automatic Seed Generation and Hybrid Classification for the Detection of Red Lesions in Digital Fundus Images, IEEE 8th International Conference on Computer and Information Technology Workshops.
Pallavi Kahai Kamesh Rao Namuduri and Hilary Thompson, Decision Support for Automated Screening of Diabetic Retinopathy, International Journal of Biomedical Imaging Volume 2006 (2006).
Reza Pourreza, Hamidreza Pourreza, Touka Banaee, Segmentation of Blood Vessels in Fundus Color Images by Radon Transform and Morphological Reconstruction, Third International Workshop on Advanced Computational Intelligence, August 25-27, 2010.
Mahdad Esmaeili, Hossein Rabbani, Alireza Mehri Dehnavi, Alireza Dehghani, A new curvelet transform based method for extraction of red lesions in digital color retinal images, Proceedings of 2010 IEEE 17th International Conference on Image Processing September 26-29, 2010.
Keerthi Ram, Gopal Datt Joshi, Jayanthi Sivaswamy, A Successive Clutter-Rejection-Based Approach for Early Detection of Diabetic Retinopathy, IEEE Transactions on Biomedical Engineering, Vol. 58, No. 3 March 2011.
T. Spencer, J. A. Olson, K. C. McHardy, P. F. Sharp, and J. V. Forrester, “An image-processing strategy for the segmentation and quantification of microaneurysms in fluorescein angiograms of the ocular fundus,” Comput. Biomed. Res., vol. 29, pp. 284–302, May 1996.
M. J. Cree, J. A. Olson, K. C. McHardy, P. F. Sharp, and J. V. Forrester, “A fully automated comparative microaneurysm digital detection system,” Eye, vol. 11, pp. 622–628, 1997.
A. J. Frame, P. E. Undrill, M. J. Cree, J. A. Olson, K. C. McHardy, P. F. Sharp, and J. Forrester, “A comparison of computer based classification methods applied to the detection of microaneurysms in ophthalmic fluorescein angiograms,” Comput. Biol. Med., vol. 28, pp. 225–238, 1998.
A. Mendonca, A. Campilho, and J. Nunes, “Automatic segmentation of microaneurysms in retinal angiograms of diabetic patients,” in Proc. Int. Conf. Image Anal. Process., 1999, pp. 728–733.
A. D. Fleming, S. Philip, and K. A. Goatman, “Automated microaneurysm detection using local contrast normalization and local vessel detection,” IEEE Trans. Med. Imag., vol. 25, no. 9, pp. 1223–1232, Sep. 2006.
M. Niemeijer, J. Staal, M. D. Abramoff, M. A. Suttorp-Schulten, and B. van Ginneken, “Automatic detection of red lesions in digital color fundus photographs,” IEEE Trans. Med. Imag., vol. 24, no. 5, pp. 584–592, May 2005.
T. Walter, P. Massin, A. Arginay, R. Ordonez, C. Jeulin, and J. C. Klein, “Automatic detection of microaneurysms in color fundus images,” Med. Image Anal., vol. 11, pp. 555–566, 2007.
L. Vincent, “Morphological area openings and closings for greyscale images,” in Proc. NATO Shape Picture Workshop, 1992, pp. 197–208.
K. Ram, G. D. Joshi, and J. Sivaswamy, “A successive clutter-rejection-based approach for early detection of diabetic retinopathy,” IEEE Trans. Biomed. Eng., vol. 58, no. 3, pp. 664–673, Mar. 2011.
B. Zhang, X. Wu, J. You, Q. Li, and F. Karray, “Detection of microaneurysms using multi-scale correlation coefficients,” Pattern Recognit., vol. 43, no. 6, pp. 2237–2248, 2010.
- There are currently no refbacks.
Please send any question about this web site to email@example.com
Copyright © 2005-2023 Praise Worthy Prize