Name
Abstract | ||
|---|---|---|
We introduce a novel method to extract the vessels in eye fundus images which is adaptive to lighting variations. In the Logarithmic Image Processing framework, a 3-segment probe detects the vessels by probing the topographic surface of an image from below. A map of contrasts between the probe and the image allows to detect the vessels by a threshold. In a lowly contrasted image, results show that our method better extract the vessels than another state-of the-art method. In a highly contrasted image database (DRIVE) with a reference, ours has an accuracy of 0.9454 which is similar or better than three state-of-the-art methods and below three others. The three best methods have a higher accuracy than a manual segmentation by another expert. Importantly, our method automatically adapts to the lighting conditions of the image acquisition. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ISBI45749.2020.9098332 | 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) |
Keywords | DocType | ISSN |
Eye fundus images,Vessel segmentation,Lighting variations,Mathematical Morphology | Conference | 1945-7928 |
ISBN | Citations | PageRank |
978-1-5386-9331-5 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Noyel Guillaume | 1 | 0 | 0.34 |
| Vartin Christine | 2 | 0 | 0.34 |
| Peter Boyle | 3 | 2 | 0.71 |
| Kodjikian Laurent | 4 | 0 | 0.34 |
| G. Noyel | 5 | 0 | 0.34 |
| P. Boyle | 6 | 0 | 0.34 |