Automatic Visual Acuity Estimation by Means of Computational Vascularity Biomarkers Using Oct Angiographies
Identificadores
Identificadores
URI: http://hdl.handle.net/20.500.11940/16071
PMID: 31683559
DOI: 10.3390/s19214732
ISSN: 1424-8220 (Electronic);1424-8220 (Linking)
Servicios
Servicios
Visualización o descarga de ficheros
Visualización o descarga de ficheros
Fecha de publicación
2019Título de revista
Sensors (Basel)
DeCS
oclusión venosa retiniana | fóvea central | agudeza visual | angiografía | algoritmos | análisis de componentes principales | reproducibilidad de resultados | humanos | tomografía | vasos sanguíneosMeSH
Retinal Vein Occlusion | Fovea Centralis | Reproducibility of Results | Humans | Blood Vessels | Visual Acuity | Principal Component Analysis | Tomography | Angiography | AlgorithmsResumen
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.
Excepto si se señala otra cosa, la licencia del ítem se describe como Atribución 4.0 Internacional
