Automatic detection of vascular bifurcations in segmented retinal images using trainable COSFIRE filters

Pattern Recognition Letters

Volumn 34, Issue 8, 2013, Pages 922-933

  Azzopardi, George ^a   Petkov, Nicolai ^a  

^a UNIVERSITY OF GRONINGEN   (Netherlands)

Author keywords

Gabor filters; Keypoint detection; Retinal fundus; Trainable filters; Vascular bifurcation

Indexed keywords

BANDPASS FILTERS; BIFURCATION (MATHEMATICS); DIGITAL STORAGE; OPHTHALMOLOGY;

AUTOMATIC CONFIGURATION; AUTOMATIC DETECTION; CARDIO-VASCULAR DISEASE; KEY-POINT DETECTORS; KEYPOINT DETECTION; RETINAL FUNDUS; RETINAL FUNDUS IMAGES; SHIFT PARAMETERS;

GABOR FILTERS;

EID: 84880927283     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2012.11.002     Document Type: Article

References (64)

1. Abramoff, M., Garvin, M., Sonka, M., 2010. Retinal imaging and image analysis. IEEE Rev. Biomed. Eng. 3, 169-208. http://dx.doi.org/10.1109/RBME. 2010.2084567, ISSN 1937-3333.
2. Aibinu, A.M., Iqbal, M.I., Shafie, A.A., Salami, M.J.E., Nilsson, M., 2010. Vascular intersection detection in retina fundus images using a new hybrid approach. Comput. Biological Med. 40 (1), 81-89. http://dx.doi.org/10.1016/j. compbiomed.2009.11.004, ISSN 0010-4825.
3. Ali, C, Hong, S., Turner, J., Tanenbaum, H., Roysam, B., 1999. Rapid automated tracing and feature extraction from retinal fundus images using direct exploratory algorithms. IEEE Trans. Inform. Technol. Biomed. 3, 125-138.
4. Ardizzone, E., Pirrone, R., Gambino, O., Radosta, S., 2008. Blood vessels and feature points detection on retinal images. In: Engineering in Medicine and Biology Society, EMBS 2008. 30th Annual Internat. Conf. IEEE, pp. 2246-2249. http://dx.doi.org/10.1109/IEMBS.2008.4649643. ISSN 1557-170X.
5. Azzopardi, G., Petkov, N., 2011. Detection of retinal vascular bifurcations by trainable V4-like filters. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (Eds.), Computer Analysis of Images and Patterns. Proc. 14th Internat. Conf. CAIP 2011, Seville, Spain, pp. 451-459. ISBN 978-3-642-23671-6.
6. Azzopardi, G., Petkov, N., 2012a. Trainable COSFIRE filters for keypoint detection and pattern recognition. IEEE Trans. Pattern Anal. Machine Intell. (99), 1. http://dx.doi.org/10.1109/TPAMI.2012.106, ISSN 0162-8828.
7. Azzopardi, G., Petkov, N., 2012b. A CORF computational model of a simple cell that relies on LGN input outperforms the Gabor function model. Biological Cybernet. 106 (3), 177-189. http://dx.doi.org/10.1007/s00422-012-0486-6, ISSN 0340-1200.
8. Becker, D., Can, A., Turner, J., Tanenbaum, H., Roysam, B., 1998. Image processing algorithms for retinal montage synthesis, mapping, and real-time location determination. IEEE Trans. Biomed. Eng. 45 (1), 105-118. http://dx.doi.org/10.1109/10.650362, ISSN 0018-9294. (Pubitemid 28053018)
9. Bevilacqua, V., Cambo, S., Cariello, L, Mastronardi, G., 2005. A combined method to detect retinal fundus features. In: Proc. of European Conf. on Emergent Aspects of Clinical Data Analysis, pp. 1-6.
10. Bhuiyan, A., Nath, B., Chua, J., Ramamohanarao, K., 2007. Automatic detection of vascular bifurcations and crossovers from color retinal fundus images. In: Third Internat. IEEE Conf. on Signal-Image Technologies and Internet-Based System (SITIS), pp. 711-718.
11. Bodis-Wollner, I., Brannan, J., 1997. Hidden visual loss in optic neuropathy is revealed using Gabor patch contrast perimetry. Clin. Neurosci. 4 (5), 284-291, ISSN 1065-6766. (Pubitemid 27382884)
12. Calvo, D., Ortega, M., Penedo, M.G., Rouco, J., 2011. Automatic detection and characterisation of retinal vessel tree bifurcations and crossovers in eye fundus images. Comput. Methods Prog. Biomed. 103 (1), 28-38. http://dx.doi.org/10.1016/j.cmpb.2010.06.002, ISSN 0169-2607.
13. Chanwimaluang, T., Guoliang, F., 2003. An efficient blood vessel detection algorithm for retinal images using local entropy thresholding. In: Proc. 2003 IEEE Internat. Symposium on Circuits and Systems (Cat. No. 03CH37430) 5, pp. 21-25.
14. Chapman, N., Dell'omo, G., Sartini, M., Witt, N., Hughes, A., Thorn, S., Pedrinelli, R., 2002. Peripheral vascular disease is associated with abnormal arteriolar diameter relationships at bifurcations in the human retina. Clin. Sci. 103, 111-116.
15. Chauduri, S., Chatterjee, S., Katz, N., Nelson, M., Goldbaum, M., 1989. Detection of blood-vessels in retinal images using tow-dimensional matched-filters. IEEE Trans. Med. Imaging 8 (3), 263-269. http://dx.doi.org/10. 1109/42.34715, ISSN 0278-0062. (Pubitemid 20617572)
16. Chen, Li, Xiang, Yang, Chen, Yaojie, Zhang, Xiao Long, 2011. Retinal image registration using bifurcation structures. In: 2011 18th IEEE Internat. Conf. on Image Processing (ICIP 2011), IEEE Signal Process. Soc, 11-14 Sept. 2011, Brussels, Belgium, pp. 2169-2172. ISBN 978-1-4577-1304-0.
17. Daugman, J., 1985. Uncertainty relation for resolution in space, spatial-frequency, and orientation optimized by two dimensional visual cortical filters. J. Opt. Soc. Amer. A - Opt. Image Sci. Vision 2 (7), 1160-1169. http://dx.doi.org/10.1364/JOSAA.2.001160, ISSN 0740-3232.
18. Du, Xiaojun, Bui, T., 2010. Retinal image segmentation based on Mumford-Shah model and Gabor wavelet filter. In: Proc. 2010 20th Internat. Conf. Pattern Recognition (ICPR 2010), IEEE Comput. Soc, Istanbul, Turkey, pp. 3384-3387. ISBN 978-0-7695-4109-9.
19. Eunhwa, J., Kyungho, H., 2006. Automatic retinal vasculature structure tracing and vascular landmark extraction from human eye image. In: Internat. Conf. on Hybrid Information Technology 7.
20. Frank, R., 2004. Diabetic retinopathy. New Engl. J. Med. 350 (1), 48-58. http://dx.doi.org/10.1056/NEJMra021678, ISSN 0028-4793. (Pubitemid 38032183)
21. Fraz, M., Remagnino, P., Hoppe, A., Velastin, S., Uyyanonvara, B., Barman, S., 2011. A supervised method for retinal blood vessel segmentation using line strength, multiscale Gabor and morphological features. In: 2011 IEEE Internat. Conf. on Signal and Image Processing Applications (ICSIPA 2011), pp. 410-415, 16-18 November 2011, Kuala Lumpur, Malaysia. ISBN 978-1-4577-0243-3.
22. Gattass, R., Sousa, A.P., Gross, CG., 1988. Visuotopic organization and extent of V3 and V4 of the macaque. J. Neurosci. 8 (6), 1831-1845.
23. Gheorghiu, E., Kingdom, F.A.A., 2009. Multiplication in curvature processing. J. Vision 9 (2). Article No. 23. http://dx.doi.org/10.1167/9.2.23.
24. Grigorescu, S.E., Petkov, N., Kruizinga, P., 2002. Comparison of texture features based on Gabor filters. IEEE Trans. Image Process. 11 (10), 1160-1167. http://dx.doi.org/10.1109/TIp.2002.804262, ISSN 1057-7149. (Pubitemid 35359387)
25. Grigorescu, C, Petkov, N., Westenberg, M.A., 2003a. The role of non-CRF inhibition in contour detection. J. Comput. Graphics Visualiz. Comput. Vision (WSCG) 11 (2), 197-204.
26. Grigorescu, C, Petkov, N., Westenberg, M.A, 2003b. Contour detection based on nonclassical receptive field inhibition. IEEE Trans. Image Process. 12 (7), 729-739.
27. Hoover, A., Kouznetsova, V., Goldbaum, M., 2000. Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Trans. Med. Imaging 19 (3), 203-210. http://dx.doi.org/10.1109/42.845178, ISSN 0278-0062.
28. Jiang, X., Mojon, D., 2003. Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Trans. Pattern Anal. Machine Intell. 25 (1), 131-137, ISSN 0162-8828.
29. Kruizinga, P., Petkov, N., 1999. Non-linear operator for oriented texture. IEEE Trans. Image Process. 8 (10), 1395-1407.
30. Martinez-Perez, M., Hughes, A., Stanton, A, Thorn, S., Chapman, N., Bharath, A., Parker, K., 2002. Retinal vascular tree morphology: A semi-automatic quantification. IEEE Trans. Biomed. Eng. 49, 912-917. (Pubitemid 34787581)
31. Mendonca, AM., Campilho, A, 2006. Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction. IEEE Trans. Med. Imaging 25 (9), 1200-1213. http://dx.doi.org/10.1109/TMI.2006. 879955, ISSN 0278-0062. (Pubitemid 44304279)
32. Moin, M., Tavakoli, H., Broumandnia, A., 2010. A new retinal vessel segmentation method using preprocessed Gabor and local binary patterns. In: 2010 6th Iranian Conf. on Machine Vision and Image Processing (MVIP), IEEE Iran Sect, Isfahan, Iran, 6 pp. ISBN 978-1-4244-9706-5.
33. Muramatsu, C, Hayashi, Y., Sawada, A., Hatanaka, Y., Hara, T., Yamamoto, T., Fujita, H., 2009. Computerized detection of retinal nerve fiber layer defects in retinal fundus images by modified polar transformation and Gabor filtering. In: Dossel, O., Schlegel, W. (Eds.), 11th International Congress of the IUPESM. Medical Physics and Biomedical Engineering. World Congress 2009. Biomedical Engineering for Audiology, Ophthalmology, Emergency & Dental Medicine, 7-12 Sept. 2009, Munich, Germany, pp. 124-126. ISBN 978-3-642-03890-7.
34. Murray, CD., 1926a. The physiological principle of minimum work applied to the angle of branching of arteries. J. Gen. Physiol. 9, 835-841.
35. Murray, CD., 1926b. The physiological principle of minimum work: I. The vascular system and the cost of blood volume. Proc. Natl. Acad. Sci. USA 12, 207-214.
36. Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abramoff, M., 2004. Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Proceedings of the SPIE - The International Society for Optical Engineering, Medical Imaging San Diego, CA, USA, pp. 648-656.
37. Ortega, M., Penedo, M.G., Rouco, J., Barreira, N., Carreira, M.J., 2009. Personal verification based on extraction and characterisation of retinal feature points. J. Vision Lang. Comput. 20 (2), 80-90. http://dx.doi.org/10. 1016/j.jvlc.2009.01.006, ISSN 1045-926X.
38. Parisi, V., Manni, G., Spadaro, M., Colacino, G., Restuccia, R, Marchi, S., Bucci, M., Pierelli, F., 1999. Correlation between morphological and functional retinal impairment in multiple sclerosis patients. Inverst. Ophthalmol. Vision Sci. 40 (11), 2520-2527, ISSN 0146-0404. (Pubitemid 29455479)
39. Pasupathy, A, Connor, C, 1999. Responses to contour features in macaque area V4. J. Neurophysiol. 82, 2490-2502.
40. Pasupathy, A., Connor, C, 2001. Shape representation in area V4: position-specific tuning for boundary conformation. J. Neurophysiol. 86, 2505-2519. (Pubitemid 34000610)
41. Pasupathy, A., Connor, C, 2002. Population coding of shape in area V4. Nat. Neurosci. 5, 1332-1338. (Pubitemid 35417769)
42. Patton, N., Aslam, T., MacGillivray, T., Deary, I., Dhillon, B., Eikelboom, R., Yogesan, K., Constable, I., 2006. Retinal image analysis: concepts, applications and potential. Prog. Retinal Eye Res. 25, 99-127. (Pubitemid 41566644)
43. Paulus, W., Schwarz, G., Werner, A., Lange, H., Bayer, A., Hofschuster, M., Muller, N., Zrenner, E., 1993. Impairment of retinal increment thresholds in huntingtons-disease. Annal. Neurol. 34 (4), 574-578. http://dx.doi.org/10.1002/ ana.410340411, ISSN 0364-5134. (Pubitemid 23289409)
44. Petkov, N., 1995. Biologically motivated computationally intensive approaches to image pattern-recognition. Future Gener. Comput. Systems 11, 451-465.
45. Petkov, N., Kruizinga, P., 1997. Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: bar and grating cells. Biological Cybernet. 76 (2), 83-96. (Pubitemid 127665169)
46. Petkov, N., Westenberg, MA, 2003. Suppression of contour perception by band-limited noise and its relation to non-classical receptive field inhibition. Biological Cybernet. 88 (10), 236-246.
47. Li, Qin, You, J., Zhang, Lei, Bhattacharya, P., 2006. A multiscale approach to retinal vessel segmentation using Gabor filters and scale multiplication. In: 2006 IEEE Conf. Systems, Man, and Cybernetics, Taipei, Taiwan, pp. 3521-3527. ISBN 1-4244-0099-6.
48. Rangayyan, R.M., Zhu, X., Ayres, F.J., Ells, A.L., 2010. Detection of the optic nerve head in fundus images of the retina with Gabor filters and phase portrait analysis. J. Digital Imag. 23 (4), 438-453. http://dx.doi.org/10.1007/ s10278-009-9261-1, ISSN 0897-1889.
49. Ricci, E., Perfetti, R., 2007. Retinal blood vessel segmentation using line operators and support vector classification. IEEE Trans. Med. Imaging 26 (10), 1357-1365. http://dx.doi.org/10.1109/TMI.2007.898551, ISSN 0278-0062. (Pubitemid 47525297)
50. Selvathi, D., Lalitha Vaishnavi, P., 2011. Gabor wavelet based blood vessel segmentation in retinal images using kernel classifiers. In: Proc. 2011 Internat. Conf. on Signal Processing, Communication, Computing and Networking Technologies (ICSCCN 2011), Thuckafay, India, pp. 830-835. ISBN 978-1-61284-653-8.
51. Shen, H., Roysam, B., Stewart, C, Turner, J., Tanenbaum, H., 2001. Optimal scheduling of tracing computations for real-time vascular landmark extraction from retinal fundus images. IEEE Trans. Inform. Technol. Biomed. 5 (1), 77-91, ISSN 1089-7771. (Pubitemid 32302935)
52. Shen, H., Stewart, C, Roysam, B., Lin, G., Tanenbaum, H., 2003. Frame-rate spatial referencing based on invariant indexing and alignment with application to online retinal image registration. IEEE Trans. Pattern Anal. Mach. Intell. 25 (3), 379-384, ISSN 0162-8828.
53. Sherman, T., 1981. On connecting large vessels to small - The meaning of Murray law. J. Gen. Physiol. 78, 431-453. (Pubitemid 11020903)
54. Soares, J.V.B., Leandro, J.J.G., Cesar Jr, R.M., Jelinek, H.F., Crée, M.J., 2006. Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification. IEEE Trans. Med. Imag. 25 (9), 1214-1222. http://dx.doi.org/10.1109/TMI.2006.879967, ISSN 0278-0062. (Pubitemid 44304280)
55. Staal, J., Abramoff, M., Niemeijer, M., Viergever, M., van Ginneken, B., 2004. Ridge-based vessel segmentation in color images of the retina. IEEE Trans. Med. Imaging 23, 501-509.
56. Sun, H., Dul, M.W., Swanson, W.H., 2006. Linearity can account for the similarity among conventional, frequency-doubling, and Gabor-based perimetric tests in the glaucomatous macula. Optometry Vision Sci. 83 (7), 455-465, ISSN 1040-5488.
57. Tsai, C, Stewart, C, Tanenbaum, H., Roysam, B., 2004. Model-based method for improving the accuracy and repeatability of estimating vascular bifurcations and crossovers from retinal fundus images. IEEE Trans. Inform. Technol. Biomed. 8, 122-130.
58. Tso, M., Jampol, L, 1982. Path-physiology of hypertensive retinopathy. Opthalmology 89, 1132-1145.
59. Usman Akram, M., Tariq, A., Nasir, S., Khan, S., 2009. Gabor wavelet based vessel segmentation in retinal images. In: 2009 IEEE Symposium on Computational Intelligence for Image Processing (CUP), 30 March-2 April 2009, Nashville, TN, USA, 4 pp. ISBN 978-1-4244-2760-4.
60. Wang, X., Ding, X., Liu, C, 2005. Gabor filters-based feature extraction for character recognition. Pattern Recognition 38 (3), 369-379. http://dx.doi.org/10.1016/j.patcog.2004.08.004, ISSN 0031-3203.
61. Yavuz, Z., Koumlse, C, 2010. Comparing 2D matched filter response and Gabor filter methods for vessel segmentation in retinal images. In: 2010 National Conf. on Electrical, Electronics and Computer Engineering (ELECO 2010), Bursa, Turkey, pp. 648-652. ISBN 978-1-4244-9588-7.
62. Yavuz, Z., Kose, C, 2011. Retinal blood vessel segmentation using Gabor filter and top-hat transform. In: 2011 IEEE 19th Signal Processing and Communications Applications Conference (SIU 2011), Antalya, Turkey, pp. 546-549. ISBN 978-1-4577-0462-8.
63. Zamir, M., Medeiros, J., Cunningham, T., 1979. Arterial bifurcations in the human retina. J. Gen. Physiol. 74 (4), 537-548. (Pubitemid 10188911)
64. Zamir, M., Sinclair, P., Wonnacott, T., 1992. Relation between diameter and flow in major branches of the arch of the aorta. J. Biomech. 25 (11), 1303-1310. http://dx.doi.org/10.1016/0021-9290(92)90285-9, ISSN 0021-9290.