Name
Title | ||
|---|---|---|
Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies. |
Abstract | ||
|---|---|---|
Optical Coherence Tomography Angiography (OCTA) constitutes a new non-invasive ophthalmic image modality that allows the precise visualization of the micro-retinal vascularity that is commonly used to analyze the foveal region. Given that there are many systemic and eye diseases that affect the eye fundus and its vascularity, the analysis of that region is crucial to diagnose and estimate the vision loss. The Visual Acuity (VA) is typically measured manually, implying an exhaustive and time-consuming procedure. In this work, we propose a method that exploits the information of the OCTA images to automatically estimate the VA with an accurate error of 0.1713. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19214732 | SENSORS |
Keywords | Field | DocType |
Optical Coherence Tomography by Angiography,Visual Acuity,Retinal Vein Occlusion,Artificial Vision,biomarkers | Computer vision,Visual acuity,Visualization,Vascularity,Fundus (eye),Electronic engineering,Foveal,Artificial intelligence,Engineering,Optical coherence tomography angiography,Artificial vision | Journal |
Volume | Issue | ISSN |
19 | 21 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Macarena Díaz | 1 | 0 | 0.34 |
| Marta Díez-Sotelo | 2 | 0 | 0.34 |
| Francisco Gómez-Ulla | 3 | 0 | 0.34 |
| Jorge Novo | 4 | 0 | 0.34 |
| Manuel Francisco G Penedo | 5 | 0 | 0.34 |
| M Ortega | 6 | 235 | 37.13 |