Retinal vessel extraction using first-order derivative of Gaussian and morphological processing

Authors:
M. M. Fraz;P. Remagnino;A. Hoppe;B. Uyyanonvara;Christopher G. Owen;Alicja R. Rudnicka;S. A. Barman
Affiliations:
Faculty of Computing, Information Systems and Mathematics, Kingston University, London, United Kingdom;Faculty of Computing, Information Systems and Mathematics, Kingston University, London, United Kingdom;Faculty of Computing, Information Systems and Mathematics, Kingston University, London, United Kingdom;Department of Information Technology, Thammasat University, Thailand;Division of Population Health Sciences and Education, St. George's, University of London, United Kingdom;Division of Population Health Sciences and Education, St. George's, University of London, United Kingdom;Faculty of Computing, Information Systems and Mathematics, Kingston University, London, United Kingdom
Venue:
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Year:
2011

Citing 10
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Abstract

The change in morphology, diameter, branching pattern and/or tortuosity of retinal blood vessels is an important indicator of various clinical disorders of the eye and the body. This paper reports an automated method for segmentation of blood vessels in retinal images by means of a unique combination of differential filtering and morphological processing. The centerlines are extracted by the application of first order derivative of Gaussian in four orientations and then the evaluation of derivative signs and average derivative values is made. The shape and orientation map of the blood vessel is obtained by applying a multidirectional morphological top-hat operator followed by bit plane slicing of a vessel enhanced grayscale image. The centerlines are combined with these maps to obtain the segmented vessel tree. The approach is tested on two publicly available databases and results show that the proposed algorithm can obtain robust and accurate vessel tracings with a performance comparable to other leading systems.