A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Localization and extraction of the optic disc using the fuzzy circular hough transform
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Comparison of Pixel and Subpixel Retinal Vessel Tree Segmentation Using a Deformable Contour Model
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Retinal vessel extraction using first-order derivative of Gaussian and morphological processing
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Fast segmentation of retinal blood vessels using a deformable contour model
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Blood vessel segmentation methodologies in retinal images - A survey
Computer Methods and Programs in Biomedicine
An approach to localize the retinal blood vessels using bit planes and centerline detection
Computer Methods and Programs in Biomedicine
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This paper presents an innovative 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 of a wide range of eye diseases. We have developed a system inspired in the classical snake but incorporating domain specific knowledge, such as blood vessels topological properties. It profites mainly from the automatic localization of the optic disc and from the extraction and enhancement of the vascular tree centerlines. Encouraging results in the detection of arteriovenous structures are efficiently achieved, as shown by the systems performance evaluation on the publicy available DRIVE database.