Title :
Retinal vessel tree segmentation using a deformable contour model
Author :
Espona, L. ; Carreira, M.J. ; Penedo, M.G. ; Ortega, M.
Author_Institution :
Electron. & Comput. Sci. Dept., Univ. of Santiago de Compostela, Santiago de Compostela
Abstract :
This paper presents an improved version of our specific methodology to detect the vessel tree in retinal angiographies. The automatic analysis of retinal vessel tree facilitates the computation of the arteriovenous index, which is essential for the diagnosis several eye diseases. The developed system is inspired in the classical snake but incorporating domain specific knowledge, such as blood vessels topological properties. It profits from the automatic localization of the optic disc, the vessel creases extraction and, as a recent innovation, the morphological vessel segmentation, all developed in our research group. After researching and testing our system, the parameter configuration has been enhanced. Significantly better results in the detection of arteriovenous structures are obtained, keeping a high efficiency, as shown by the systems performance evaluation on the publicly available DRIVE database.
Keywords :
diseases; eye; feature extraction; image segmentation; medical image processing; patient diagnosis; DRIVE database; deformable contour model; eye disease diagnosis; retinal angiographies; retinal vessel tree segmentation; vessel creases extraction; Angiography; Blood vessels; Databases; Deformable models; Diseases; Retina; Retinal vessels; System performance; System testing; Technological innovation;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761762