Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72849-8_23 | IbPRIA (2) |
Keywords | Field | DocType |
blood vessels topological property,automatic localization,retinal vessel tree,arteriovenous index,vascular tree centerline,vessel tree,automatic analysis,arteriovenous structure,retinal vessel segmentation,classical snake,retinal angiographies,indexation,profitability,system performance | Computer vision,Vessel segmentation,Pattern recognition,Computer science,Optic disc,Artificial intelligence,Retinal,Computation | Conference |
Volume | ISSN | Citations |
4478 | 0302-9743 | 13 |
PageRank | References | Authors |
0.72 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| L. Espona | 1 | 14 | 1.09 |
| María J. Carreira | 2 | 134 | 9.81 |
| M Ortega | 3 | 235 | 37.13 |
| Manuel G. Penedo | 4 | 284 | 24.93 |