Abstract
Optical Coherence Tomography (OCT) is one of the most advanced, non-invasive method of eye examination. Age-related macular degeneration (AMD) is one of the most frequent reasons of acquired blindness. Our aim is to develop automatic methods that can accurately identify and characterize biomarkers in OCT images, related to AMD. We present methods for quantizing hyperreflective foci (HRF) with deep learning. We also describe an algorithm for determining pigmentepithelial detachment (PED) and localizing outer retinal tubulation (ORT) that appears between the layers of the retina.
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Katona, M., Kovács, A., Varga, L., Grósz, T., Dombi, J., Dégi, R., & Nyúl, L. G. (2018). Automatic Detection and Characterization of Biomarkers in OCT Images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10882 LNCS, pp. 706–714). Springer Verlag. https://doi.org/10.1007/978-3-319-93000-8_80
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