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Segmentation of retinal fluids and hyperreflective foci using deep learning approach in optical coherence tomography scans
(SPIE, 2020)
Retinal diseases are a common cause of blindness around the world, early detection of clinical findings can help to avoid vision loss in patients. Optical coherence tomography images have been widely used to diagnose retinal ...
Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography
(Elsevier, 2019)
Background and objectives: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical ...
Hybrid Deep Learning Gaussian Process for Diabetic Retinopathy Diagnosis and Uncertainty Quantification
(Springer Science, 2020)
La retinopatía diabética (RD) es una de las complicaciones microvasculares de la diabetes mellitus, que sigue siendo una de las principales causas de ceguera en todo el mundo. Los modelos computacionales basados en redes ...
A lightweight deep learning model for mobile eye fundus image quality assessment
(SPIE, 2020)
Image acquisition and automatic quality analysis are fundamental stages and tasks to support an accurate ocular diagnosis. In particular, when eye fundus image quality is not appropriate, it can hinder the diagnosis task ...