Name
Abstract | ||
|---|---|---|
In this paper, we present an algorithm to detect the presence of diabetic retinopathy (DR)-related lesions from fundus images based on a common analytical approach that is capable of identifying both red and bright lesions without requiring specific pre- or postprocessing. Our solution constructs a visual word dictionary representing points of interest (PoIs) located within regions marked by speci... |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/TBME.2012.2201717 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Lesions,Dictionaries,Visualization,Retina,Training,Diabetes,Retinopathy | Computer vision,Computer science,Visualization,Fundus (eye),Image quality,Artificial intelligence,Contextual image classification,Image resolution,Cross-validation,Visual dictionary,Visual Word | Journal |
Volume | Issue | ISSN |
59 | 8 | 0018-9294 |
Citations | PageRank | References |
33 | 1.08 | 20 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anderson Rocha | 1 | 913 | 69.11 |
| Tiago Jose de Carvalho | 2 | 50 | 2.02 |
| Herbert F. Jelinek | 3 | 477 | 36.78 |
| Siome Goldenstein | 4 | 618 | 47.43 |
| Jacques Wainer | 5 | 912 | 89.74 |