Name
Abstract | ||
|---|---|---|
This paper describes a new approach to determine vascular skeleton in retinal images. This approach is based on mathematical morphology along with curvature evaluation. In particular, a variant of the watershed transformation, the stochastic watershed, is applied to extract the vessel center-line. Its goal is to obtain directly the skeleton of the retinal tree avoiding a previous stage of vessel segmentation in order to reduce the dependence between stages and the computational cost. Experimental results show qualitative improvements if the proposed method is compared with other state-of-the-art algorithms, above all on pathological images. Therefore, the result of this work is an efficient and effective vessel centerline extraction algorithm and can be useful for further applications and image-aided diagnosis systems. |
Year | Venue | Keywords |
|---|---|---|
2014 | Signal Processing Conference | image segmentation,mathematical morphology,medical image processing,retinal recognition,curvature evaluation,image-aided diagnosis systems,mathematical morphology,pathological images,retinal images,retinal network skeleton determination,retinal vascular skeleton determination,stochastic watershed transformation,vessel centerline extraction algorithm,vessel segmentation,Retinal vascular skeleton,curvature evaluation,mathematical morphology,stochastic watershed,vessel centerline |
Field | DocType | ISSN |
Vessel segmentation,Computer vision,Curvature,Mathematical morphology,Computer science,Extraction algorithm,Artificial intelligence,Retinal,Skeleton (computer programming) | Conference | 2076-1465 |
Citations | PageRank | References |
1 | 0.37 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandra Morales | 1 | 16 | 4.16 |
| Naranjo, V. | 2 | 6 | 1.83 |
| Jesús Angulo | 3 | 7 | 2.20 |
| Lopez-Mir, F. | 4 | 2 | 1.07 |