TY  - JOUR
VL  - 10882
TI  - Automatic Detection and Characterization of Biomarkers in OCT Images
JF  - LECTURE NOTES IN COMPUTER SCIENCE
A1  -  Katona Melinda
A1  -  Kovács Attila
A1  -  Varga László
A1  -  Grósz Tamás
A1  -  Dombi József
A1  -  Dégi Rózsa
A1  -  Nyúl László Gábor
SP  - 706
Y1  - 2018///
UR  - https://doi.org/10.1007/978-3-319-93000-8_80
N1  - A sorozat rendelkezik IF [és vagy] SJR értékkel a cikk megjelenési évében, ezért besorolása lehet szakcikk a központi MTMT adminisztrátorokkal történt egyeztetés alapján. (NM, SZTE admin5, 2023.05.26.)
ID  - publicatio28509
AV  - public
SN  - 0302-9743
EP  - 714
N2  - 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.
ER  -