Blood Vessel Enhancement and Segmentation for Screening of Diabetic Retinopathy

M. Usman Akram, Ibaa Jamal, Anam Tariq

Abstract


Diabetic retinopathy is an eye disease caused by the increase of insulin in blood and it is one of the main cuases of blindness in idusterlized countries. It is a progressive disease and needs an early detection and treatment. Vascular pattern of human retina helps the ophthalmologists in automated screening and diagnosis of diabetic retinopathy. In this article, we present a method for vascular pattern ehnacement and segmentation. We present an automated system which uses wavelets to enhance the vascular pattern and then it applies a piecewise threshold probing and adaptive thresholding for vessel localization and segmentation respectively. The method is evaluated and tested using publicly available retinal databases and we further compare our method with already proposed techniques. 


Full Text:

PDF

References


. EJ Susman, WJ Tsiaras, KA Soper: Diagnosis of Diabetic Eye Disease. JAMA. 1982; 247: 3231-3234.

. SC Lee, ET Lee, RM Kingsley, YWang, D Russell, R Klein, A Wanr. Comparison of Diagnosis of Early Retinal Lesions of Diabetic Retinopathy between a Computer System and Human Experts. Graefes Arch. Clin. Exp. Ophtalmol. 2001; 119: 509-515.

. C Sinthanayothin, JF Boyce, HL Cook, TH Williamson. Automated Localization of the Optic Disc. Fovea and Retinal Blood Vessels from Digital Color Fundus Images. Br. J. Opthalmol. 1999; 83: 231-238.

. J KansKy. Clinical Opthalmology. London: Butterworh-Heinmann. 1994.

. M Foracchia, E Grisan, A Ruggeri. Detection of Optic Disc in Retinal Images by Means of a Geometrical Model of Vessel Structure. IEEE Transactions on Medical Imaging. 2004; 23(10): 1189-1195.

. NKMN Subhasis Chaudhuri, Shankar Chatterjee, Michael Goldbaum. Detection of Blood Vessels in Retinal Images using Two-Dimensional Matched Filters. IEEE Transactions on Medical Imaging. 1989; 8(3): 263-269.

. T Spencer, RP Phillips, PF Sharp, JV Forrester. Automated Detection and Quantification of Microaneurysms in Fluorescein Angiograms. Graefes Arch. Clin. Exp. Ophtalmol. 1991; 230: 36-41.

. AJ Frame, PE Undill, MJ Cree, JA Olson, KC McHardy, PF Sharp, JF Forrester. A Comparison of Computer Based Classification Methods Applied to the Detection of Microaneurysms in Ophtalmic Fluorescein Angiograms. Comput. Biol. Med. 1998; 28: 225-238.

. A Osareh, M Mirmehdi, B Thomas, R Markham. Automatic Recognition of Exudative Maculopathy using Fuzzy C-Means Clustering and Neural Networks. Proc. Medical Image Understanding Analysis Conference. 2001: 49-52.

. R Phillips, J Forrester, P Sharp. Automated Detection and Quantification of Retinal Exudates. Graefes Arch. Clin. Exp. Ophtalmol. 1993; 231: 90-94.

. T Teng, M Lefley, D Claremont. Progress towards Automated Diabetic Ocular Screening: A Review of Image Analysis and Intelligent Systems for Diabetic Retinopathy. Med. Biol. Eng. Comput. 2002; 40: 2-13.

. A Pinz, S Bernogger, P Datlinger, A Kruger. Mapping the Human Retina. IEEE Trans. Med. Imag. 1998; 17(4): 606-619.

. CL Tsai, CV Stewart, HL Tanenbaum, B Roysam. Modelbased Method for Improving the Accuracy and Repeatability of Estimating Vascular Bifurcations and Crossovers from Retinal Fundus Images. IEEE Trans. Inf. Technol. Biomed. 2004; 8(2): 122-130.

. H Li, O Chutatape. Automated Feature Extraction in Color Retinal Images by a Model Based Approach. IEEE Trans. Biomed. Eng. 2004; 51(2): 246-254.

. AM Mendona, AJ Campilho. Segmentation of Retinal Blood Vessels by Combining the Detection of Centerlines and Morphological Reconstruction. IEEE Trans. Med. Imag. 2006; 25(9): 1200-1213.

. I Liu, Y Sun. Recursive Tracking of Vascular Networks in Angiograms Based on the Detection-Deletion Scheme. IEEE Trans. Med. Imag. 1993; 12(2): 334-341.

. L Zhou, MS Rzeszotarski, LJ Singerman, JM Chokreff. The Detection and Quantification of Retinopathy using Digital Angiograms. IEEE Trans. Med. Imag. 1994; 13(4): 619-626.

. O Chutatape, L Zheng, SM Krishnan. Retinal Blood Vessel Detection and Tracking by Matched Gaussian and Kalman Filters. Proc. 20th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. (EMBS98). 1998; 20: 3144-3149.

. YA Tolias, SM Panas. A Fuzzy Vessel Tracking Algorithm for Retinal Images Based on Fuzzy Clustering. IEEE Trans. Med. Imag. 1998; 17(2): 263-273.

. A Can, H Shen, JN Turner, HL Tanenbaum, B. Roysam. Rapid Automated Tracing and Feature Extraction from Retinal Fundus Images using Direct Exploratory Algorithms. IEEE Trans. Inf. Technol. Biomed. 1999; 3(2): 125-138.

. M Lalonde, L Gagnon, MC Boucher. Non-Recursive Paired Tracking for Vessel Extraction from Retinal Images. Vision Interface. 2000: 61-68.

. T McInerney, D Terzopoulos. T-snakes: Topology Adaptive Snakes. Med. Image Anal. 2000; 4: 73-91.

. R Toledo, X Orriols, X Binefa, P Radeva, J Vitri, J Villanueva. Tracking of Elongated Structures using Statistical Snakes. IEEE Comput. Soc. Conf. Comput. Vision Pattern Recog. (CVPR). 2000.

. A Vasilevskiy, K Siddiqi. Flux Maximizing Geometric Flows. IEEE Trans. Pattern Anal. Mach. Intell. 2002; 24(12): 1565-1578.

. D Nain, A Yezzi, G Turk. Vessel Segmentation using a Shape Driven Flow. Med. Image Comput. Comput.-Assist. Intervention MICCAI. 2004: 51-59.

. S Chaudhuri, S Chatterjee, N Katz, M Nelson, M Goldbaum. Detection of Blood Vessels in Retinal Images using Two-Dimensional Matched Filters. IEEE Trans. Med. Imag. 1989: 263-269.

. J Staal, MD Abramoff, M Niemeijer, MA Viergever, B van Ginneken. Ridge-Based Vessel Segmentation in Color Images of the Retina. IEEE Trans. Med. Imag. 2004; 23(4): 501-509.

. A Hoover, V Kouznetsova, M Goldbaum. Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Trans. Med. Imag. 2000; 19(3): 203-211.

. A Arnodo, N Decoster and SG Roux. A wavelet-based method for multifractal image analysis. I. Methodology and test applications on isotropic and anisotropic random rough surfaces. Eur. Phys. J. A. 2000; 15: 567-600.

. JP Antoine, P Carette, R Murenzi, B Piette. Image analysis with two-dimensional continuous wavelet transform. Signal Process. 1993; 31: 241-272.

. JVB Soares, JJG. Leandro RM. Cesar HF Jelinek, J Cree. Retinal vessel segmentation using the 2-D gabor wavelet and supervised classification. IEEE Trans. on Med. Imag. 2006; 25(9): 1214-1222.

. Niemeijer, van Ginneken, B. http://www.isi.uu.nl/Reseach/Databases/DRIVE/results.php, 2002

. Hoover: STARE database, http://www.ces.clemson.edu/ ahoover/stare

. Kauppi T, Kalesnykiene V, Kamarainen JK, Lensu L, Sorri I, Raninen A, Voutilainen R, Uusitalo H, Klviinen H, Pietil J. DIARETDB1 diabetic retinopathy database and evaluation protocol, Technical report, (2006).

. Tama BA, Rodiyatul FS, Hermansyah. An Early Detection Method of Type-2 Diabetes-Mellitus in Public Hospital. TELKOMNIKA. 2011; 9(2): 287-294.

. Kusuma H, Wirawan, Soeprijanto A. Gabor-based Face Recognition with Illumination Variation using Subspace-Linear Discriminant Analysis. TELKOMNIKA. 2012; 10(1): 119-128.




DOI: http://dx.doi.org/10.12928/telkomnika.v10i2.802

Article Metrics

Abstract view : 235 times
PDF - 248 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Universitas Ahmad Dahlan

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

View TELKOMNIKA Stats