%T Automatic Detection and Characterization of Biomarkers in OCT Images
%A  Katona Melinda
%A  KovĂĄcs Attila
%A  Varga LĂĄszlĂł
%A  GrĂłsz TamĂĄs
%A  Dombi JĂłzsef
%A  DĂŠgi RĂłzsa
%A  NyĂşl LĂĄszlĂł GĂĄbor
%P 706-714
%L publicatio28509
%I szte
%J LECTURE NOTES IN COMPUTER SCIENCE
%O A sorozat rendelkezik IF [ĂŠs vagy] SJR ĂŠrtĂŠkkel a cikk megjelenĂŠsi ĂŠvĂŠben, ezĂŠrt besorolĂĄsa lehet szakcikk a kĂśzponti MTMT adminisztrĂĄtorokkal tĂśrtĂŠnt egyeztetĂŠs alapjĂĄn. (NM, SZTE admin5, 2023.05.26.)
%X 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.
%R MTMT:3389828 10.1007/978-3-319-93000-8_80
%V 10882
%D 2018