Fast Localization of the Optic Disc in Retinal Images Using Intensity and Vascular Information

J. Benadict Raja(1*), C. G. Ravichandran(2)

(1) Department of Computer Science and Engineering, PSNA College of Engineering and Technology, Dindigul, T. N., India
(2) Excel Engineering College, Komarapalayam, T. N., India
(*) Corresponding author


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Abstract


Optic Disc (OD) localization is an important step in retinal image analysis especially for grading Diabetic retinopathy and Glaucoma. This paper describes a method to automatically localize the OD position in retinal fundus images. The method localizes the OD by combining intensity and vascular information. Initially, the vascular structure is extracted using 2 dimensional Gabor filtering followed by a simple thresholding technique. Then the initial OD candidates are selected using intensity information. The candidates’ satisfying area and density criterion are considered for the final stage. In the final stage, the entropy of vascular directions on the final candidates was calculated, and the candidate having maximum and optimum entropy was considered as OD region. The proposed method was evaluated on the two publicly available DRIVE and STARE databases. The method was able to obtain 100% of OD localization accuracy on DRIVE database with 2.2 seconds average computation time.
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Keywords


Retinal Image Analysis; Optic Disc Localization; Glaucoma

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References


K.G. Alberti, P.Z. Zimmet, Definition, diagnosis and classification of diabetes mellitus and its complications, part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet. Med. , vol. 15 no. 7,1998, pp. 539–553.

R.N. Frank, Diabetic retinopathy. Prog. Retin. Eye Res. , vol. 14 no. 2,1995, pp. 361–392.

O. Faust, U.R. Acharya, E.Y.K. Ng, K.H. Ng, J.S. Suri, Algorithms for the automated detection of diabetic retinpathy using digital fundus images: A review, J Med Syst, vol. 36 no. 1,2012, pp. 145-157.

A. Hoover, M. Gold Baum , Locating the Optic Nerve in a Retinal Image Usingthe Fuzzy Convergence of the Blood Vessels, IEEE Transactions on Medical Imaging, vol. 22 no. 8,2003,pp. 951-958.

J. Lowell, A. Hunter, D. Steel, A. Basu, R. Ryder, E. Fletcher, L. Kennedy, Optic nerve head segmentation, IEEE Transactions on Medical Imaging, vol. 23 no. 2,2004,pp. 256-264.

DRIVE: Digital Retinal Images for Vessel Extraction. URL:/http://www.isi.uu.nl/Research/Databases/DRIVE/S

M.R.K. Mookiah, U.R. Acharya, C.K. Chua, .M. Lim, E.Y.K. Ng, A. Lude, Computer-aided diagnosis of diabetic retinopathy: A review, Computers in Biology and Medicine, vol. 43 no. 1,2013, pp. 2136-2155.

M. S. Haleem, L. Han, J. Hemert, B. Li ,Automatic extraction of retinal features from colour retinal images for glaucoma diagnosis: A review, Computerized medical imaging and graphics, vol. 37 no. 1,2013, pp. 581-596.

C. Sinthanayothin, J.F. Boyce, H.L. Cook, T. H. Williamson, Automated localization of the optic disc, fovea, and retinal blood vessels from digital colour fundus images, Br J Opthalmal, vol. 83 no. 8,1999,pp. 902-910.

T. Walter, J.C. Klein, Segmentation of color fundus images of the human retina: detection of the optic disc and the vascular tree using morphological techniques, in: Proc. 2nd Int. Symp. Med. Data Anal., 2001, pp. 282–287.

H.K Hsiao, C.C. Liu, C.Y. Yu, S.W. Kuo, S.S. Yu, A novel optic disc detection scheme on retinal images, Expert Systems with Applications, vol. 39 no. 1,2012,pp. 10600–10606.

F.T. Haar, Automatic localization of the optic disc in digital clolour images of the human retina, M.S thesis, Utrecht University, Utrecht, The Netherlands, 2005.

D.A. Godse, D.S. Bormane, Automated Localization of Optic Disc in Retinal Images, International Journal of Advanced Computer Science and Applications, vol. 4 no. 2,2013, pp. 65-71.

M. Lalonde, M. Beaulieu, L. Gagnon, Fast and robust optic disc detection using pyramidal decomposition and Hausdorff-based template matching, IEEE Trans. Med. Imaging, vol. 20 no. 11,2001, pp. 1193–1200.

A. Osareh, M. Mirmehdi, B. Thomas, R. Markham, Automated identification of Diabetic Retinal Exudates in digital colour images, Br J Opthalmal, vol. 87 no. 10,2003,pp. 1220-1223.

A. Dehghani, H.A. Moghaddam, M.S. Moin, Optic disc localization in retinal images using histogram matching, EURASIP Journal on Image and Video Processing,2012

S.A. Ramakanth, R.V. Babu, Approximate nearest neighbor field based optic disk detection, Computerized medical imaging and graphics, vol. 38 no. 1,2014,pp. 49-56.

H. Yu, E.S. Barriga, C. Agurto, S. Echegaray, M.S. Pattichis, W. Bauman, P. Soliz, Fast localization and segmentation of optic disk in retinal images using directional matched filtering and level sets, IEEE Transactions on information technology in biomedicine, vol. 16 no.4,2012, pp. 644-657.

H. Li, O.Chutatape, Automated feature extraction in color retinal images by a model based approach, IEEE Transactions on Biomedical Engineering, vol. 5 no. 2,2004,pp. 246-254.

A. Sopharak, B. Uyyanovara, S. Barmanb, T.H. Williamson, Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods, Computerized medical imaging and graphics, vol. 32 no. 1,2008, pp. 720-727.

S. Lu, Accurate and efficient optic disc detection and segmentation by a circular transformation, IEEE Transactions on medical imaging, vol. 30 no. 2,2011, pp. 2126-2133.

A.D. Fleming, K.A. Goatman, S. Philip, J.A. Olson, P.F. Sharp, Automatic detection of retinal anatomy to assist diabetic retinopathy screening, Phys. Med. Biol. , vol. 52 no. 1,2007, pp. 331-.

X. Zhu, R.M. Rangayyan, A.L. Ells, Detection of the optic nerve head in fundus images of the retina using the hough transform for circles. J. Digit. Imag., vol. 23 no. 3,2010, pp. 332–341.

S. Lu, J.H. Lim, Automatic optic disc detection from retinal images by a line operator, IEEE Transactions on Biomedical Engineering, vol. 58 no. 1,2011,pp. 88-94.

A. Youssif, A.Z. Ghalwash, A. Ghoneim, Optic disc detection from normalized digital fundus images by means of a vessels direction matched filter, IEEE Trans. Med. Imag. vol. 27 no. 1,2008,pp. 11-18.

M. Foracchia, E. Grisan, A. Ruggeri, Detection of optic disc in retinal images by means of a geometrical model of vessel structure, IEEE Trans. Med. Imaging , vol. 23 no. 10,2004, pp. 1189–1195.

A.E. Mahfouz, A.S. Fahmy, Fast Localization of the optic disc using projection of image features, IEEE Transactions on Image Processing, vol. 19 no. 12,2010,pp. 3285-3289.

R.M. Rangayyan, X. Zhu, F.J. Ayres, A.L. Ells, Detection of the optic nerve head in fundus images of the retina with Gabor filters and phase portrait analysis. J. Digit. Imag., vol. 23 no. 4,2010, pp. 438–453.

A.M. Mendonca¸ A. Sousaa, L. Mendonca, A. Campilho , Automatic localization of the optic disc by combining vascular and intensity information, Computerized Medical Imaging and Graphics , vol. 37 no. 1,2013,pp. 409-417.

M. Niemeijer, M.D. Abràmoff, B.V. Ginneken, Fast detection of the optic disc and fovea in color fundus photographs, Medical Image Analysis, vol. 13 no. 1,2009,pp. 859–870.

H. Ying, M. Zhang , J-C. Liu, Fractal-based automatic localization and segmentation of optic disc in retinal images. In: Proceedings of the 29th Annual International Conference of the IEEE EMBS. 2007, pp. 4139–4141.

D. Welfer, J. Scharcanski, C.M. Kitamura, M.M.D. Pizzol, L.W.B. Ludwig, D.R. Marinho, Segmentation of the optic disk in color eye fundus images using an adaptive morphological approach, Computers in biology and medicine, vol. 40 no. 1,2010, pp. 124-137.

M. Park, J.S. Jin, S. Luo, Locating the optic disc in retinal images, in: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation, IEEE, Sydney, Australia, 2006, pp. 14 –145.

K.W. Tobin, E. Chaum, V.P. Govindasamy, T.P. Karnowski, Detection of anatomic structures in human retinal imagery, IEEE Transactions on Medical Imaging , vol. 26 no. 12,2007, pp. 1729-1739.

S. Ravishankar, A. Jain, A. Mittal, Automated feature extraction for early detection of diabetic retinopathy in fundus images, in: IEEE Conference on Computer Vision and Pattern Recognition, 2009, pp. 210–217.

C.G.Ravichandran, J.Benadict Raja, A fast enhancement/thresholding based blood vessel segmentation for retinal image using contrast limited adaptive histogram equalization, J.Med. Imaging Health Inf., 4,2014, pp. 567-575.

Chauhan, R., Manocha, P., Chandwani, G., Retinal vessel extraction and vessel path prediction by active contouring, (2014) International Review on Computers and Software (IRECOS), 9 (3), pp. 450-45.

Karthikeyan, S., Rengarajan, N., Hybrid feature analysis for assessment of glaucoma using RNFL defects, (2014) International Review on Computers and Software (IRECOS), 9 (1), pp. 178-18.


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