Abstract
This paper presents a comparison of pixel and subpixel performance of the snake-based system designed to detect the vessel tree in eye fundus images. The automatic analysis of the retinal vessel tree facilitates the computation of the arteriovenous index, which is essential for the diagnosis and evolution of several eye diseases. A high accuracy is required to correctly assess the clinicians and it is insufficient when working at a pixel level. The developed model is inspired in the classical snake but incorporating domain specific knowledge and profits from the automatic localization of the optic disc and from the extraction of vascular tree centerlines previously developed in our research group [1]. The efficiency and accuracy of the detection of arteriovenous structures are evaluated using the publicly available DRIVE database and an equivalent system configuration for pixel and subpixel results. Results demonstrate that, although more time consuming, subpixel retinal vessel extraction is much more reliable, keeping relatively low values of computing time.
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Caderno, I.G., Penedo, M.G., Mariño, C., Carreira, M.J., Gómez-Ulla, F., González, F.: Automatic Extraction of the Retina AV Index. In: Campilho, A.C., Kamel, M. (eds.) ICIAR 2004. LNCS, vol. 3212, pp. 132–140. Springer, Heidelberg (2004)
Niemeijer, M., van Ginneken, B., Staal, J., Suttorp-Schulten, M.S.A., Abràmoff, M.D.: Automatic Detection of Red Lesions in Digital Color Fundus Photographs. IEEE Transactions on Medical Imaging 24(5), 584–592 (2005)
Aurell, E.: A Note of Signs in the Fundus Oculi Hypertension Conventional Assessment and Significance. Bull. World Health Organ. 34, 955–960 (1967)
Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abràmoff, M.D.: Comparative Study of Retinal Vessel Segmentation Methods on a new Publicy Avaliable Database. In: Proceedings of the SPIE. Medical Imaging 2004: Image Processing, vol. 5370, pp. 648–656 (2004)
Mendoça, A.M., Campilho, A.: Segmentation of Retinal Blood Vessels by Combining the Detection of Centerlines and Morphological Reconstruction. IEEE Transactions on Medical Imaging 25(9), 1200–1213 (2006)
Soares, J.V.B., Leandro, J.J.G., Cesar Jr., R.M.C., Jelinek, H.F., Cree, M.J.: Retinal Vessel Segmentation Using the 2-D Gabor Wavelet and Supervised Classification. IEEE Transactions on Medical Imaging 25(9), 1214–1222 (2006)
Toledo, R., Orriols, X., Binefa, X., Redeva, P., Vitriá, J., Villanueva, J.J.: Tracking elongated structures using statistical snakes. In: Proceedings IEEE Conference on Computer Vision and Pattern Recognition, vol. 1(1), pp. 157–162 (2000)
Phaml, T.D., Tran, D.T., Brown, M., Lee Kennedy, R.: Image Segmentation of Retinal Vessels by Fuzzy Models. In: Proceedings of International Symposium on Intelligent Signal Processing and Communication Systems (2005)
Staal, J.J., Abràmoff, M.D., Niemeijer, M., Viergever, M.A., van Ginneken, B.: Ridge based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging 23, 501–509 (2004)
Espona, L., Carreira, M.J., Ortega, M., Penedo, M.G.: A Snake for Retinal Vessel Segmentation. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds.) IbPRIA 2007. LNCS, vol. 4478, pp. 178–185. Springer, Heidelberg (2007)
Ortega, M., Mariño, C., Penedo, M.G., Blanco, M., González, F.: Personal Authentication based on Feature Extraction and Optic Nerve Location in Digital Retinal Images. Wseas Transactions on Computers 5(6), 1169–1176 (2006)
Kass, M., Witkin, A., Terzopoulos, D.: Active Contour Models. International Journal of Computer Vision 1(2), 321–331 (1998)
Blanco, M., Penedo, M.G., Barreira, N., Penas, M., Carreira, M.J.: Localization and Extraction of the Optic Disc using the Fuzzy Circular Hough Transform. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 713–721. Springer, Heidelberg (2006)
Canny, J.: A Computational Approach to Edge-Detection. IEEE Transactions on Pattern Analysis and Machine Inteligence 8(6), 679–689 (1986)
Niemeijer, van Ginneken, B.: Image Sciences Institute.DRIVE: Results Browser (2002), http://www.isi.uu.nl/Research/Databases/DRIVE/browser.php
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Espona, L., Carreira, M.J., Penedo, M.G., Ortega, M. (2008). Comparison of Pixel and Subpixel Retinal Vessel Tree Segmentation Using a Deformable Contour Model. In: Ruiz-Shulcloper, J., Kropatsch, W.G. (eds) Progress in Pattern Recognition, Image Analysis and Applications. CIARP 2008. Lecture Notes in Computer Science, vol 5197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85920-8_83
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DOI: https://doi.org/10.1007/978-3-540-85920-8_83
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