Name
Abstract | ||
|---|---|---|
•A supervised retinal artery/vein classification technique is proposed.•The method extracts 455 features from each vessel centerline pixel.•It selects the optimal feature set for the classification on many kinds of images.•Its performance is better than the state-of-the-art graph-based methods.•It provides a better entry to the artery/vein classification using graph analysis. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.cmpb.2018.04.016 | Computer Methods and Programs in Biomedicine |
Keywords | Field | DocType |
Fundus image,Artery/vein classification,Genetic search feature selection | Computer vision,Feature selection,Computer science,Retinal Artery,Image quality,Fundus (eye),Power graph analysis,Pixel,Artificial intelligence,Genetic search,Image resolution | Journal |
Volume | ISSN | Citations |
161 | 0169-2607 | 5 |
PageRank | References | Authors |
0.44 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fan Huang | 1 | 11 | 1.90 |
| Behdad Dashtbozorg | 2 | 110 | 10.31 |
| Tao Tan | 3 | 46 | 10.25 |
| Bart M. Ter Haar Romeny | 4 | 1444 | 227.69 |