Abstract
Extraction of blood vessels within the retina is an important task that can help in detecting a number of diseases, including diabetic retinopathy. Current techniques achieve good, but not perfect performance and this suggests that improved preprocessing may be needed. The image ray transform is a method to highlight tubular features (such as blood vessels) based upon an analogy to light rays. The transform has been employed to enhance retinal images from the DRIVE database, and a simple classification technique has been used to show the potential of the transform as a preprocessor for other supervised learning techniques. Results also suggest potential for using the ray transform to detect other features in the fundus images, such as the fovea and optic disc.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chaudhuri, S., Chatterjee, S., Katz, N., Nelson, M., Goldbaum, M.: Detection of blood vessels in retinal images using two-dimensional matched filters. IEEE Transactions on Medical Imaging 8, 263–269 (1989)
Zana, F., Klein, J.: Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation. IEEE Transactions on Image Processing 10, 1010–1019 (2001)
Jiang, X., Mojon, D.: Adaptive local thresholding by verification-based multithreshold probing with application to vessel detection in retinal images. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 131–137 (2003)
Staal, J., Abramoff, M., Niemeijer, M., Viergever, M., van Ginneken, B.: Ridge based vessel segmentation in color images of the retina. IEEE Transactions on Medical Imaging 23, 501–509 (2004)
Soares, J., Leandro, J., Cesar Jr., R., Jelinek, H., Cree, M.: Retinal vessel segmentation using the 2-D Morlet wavelet and supervised classification bas. IEEE Transactions on Medical Imaging 25, 1214–1222 (2006)
Niemeijer, M., Staal, J., van Ginneken, B., Loog, M., Abramoff, M.: Comparative study of retinal vessel segmentation methods on a new publicly available database. In: Proc. SPIE Medical Imaging 2004, pp. 648–656 (2004)
Al-Rawi, M., Qutaishat, M., Arrar, M.: An improved matched filter for blood vessel detection of digital retinal images. Computers in Biology and Medicine 37, 262–267 (2007)
Zhang, B., Zhang, L., Zhang, L., Karray, F.: Retinal vessel extraction by matched filter with first-order derivative of Gaussian. Computers in Biology and Medicine 40, 438–445 (2010)
Nixon, M.S., Liu, X.U., Direkoglu, C., Hurley, D.J.: On using physical analogies for feature and shape extraction in computer vision. The Computer Journal (2009)
Perona, P., Malik, J.: Scale-space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence 12, 629–639 (1990)
Liu, X.U., Nixon, M.: Medical image segmentation by water flow. In: Proc. Medical Image Understanding and Analysis (MIUA 2007) (2007)
Maragos, P.: PDEs for morphological scale-spaces and eikonal applications. In: Bovik, A.C. (ed.) The Image and Video Processing Handbook, 2nd edn., pp. 587–612. Elsevier Academic Press (2005)
Cummings, A.H., Nixon, M.S., Carter, J.N.: Circle detection using the image ray transform. In: Int’l Conf. Computer Vision Theory and Applications, VISAPP 2010 (2010)
Cummings, A.H., Nixon, M.S., Carter, J.N.: A novel ray analogy for enrolment of ear biometrics. In: 4th IEEE Int’l Conf. on Biometrics Theory, Applications Systems, BTAS 2010 (2010)
Hill, F.: Computer graphics using OpenGL, 3rd edn., ch. 12, p. 678. Prentice Hall, Englewood Cliffs (2000)
Niemeijer, M., Abrāmoff, M., van Ginneken, B.: Fast detection of the optic disc and fovea in color fundus photographs. Medical Image Analysis 13, 859–870 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cummings, A.H., Nixon, M.S. (2010). Retinal Vessel Extraction with the Image Ray Transform. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-17274-8_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17273-1
Online ISBN: 978-3-642-17274-8
eBook Packages: Computer ScienceComputer Science (R0)