Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies

Díaz González, Macarena; Díez Sotelo, Marta; Gómez-Ulla, Francisco; Novo Buján, Jorge; Penedo, Manuel; Ortega Hortas, Marcos

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http://hdl.handle.net/2183/24542

Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies

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M.Díaz_Automatic_Visual_Acuity_Estimation_by_Means_of_Computational_Vascularity_Biomarkers_Using_Oct_Angiographies_2019.pdf (3.49 MB)

Identifiers

URI: http://hdl.handle.net/2183/24542

DOI: 10.3390/s19214732

Publication date

2019-10-31

Authors

Díaz González, Macarena

Díez Sotelo, Marta

Gómez-Ulla, Francisco

Novo Buján, Jorge

Penedo, Manuel

Ortega Hortas, Marcos

Bibliographic citation

Díaz, M.; Díez-Sotelo, M.; Gómez-Ulla, F.; Novo, J.; Penedo, M.F.G.; Ortega, M. Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies. Sensors 2019, 19, 4732.

Abstract

[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.