RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge.
Hrvoje BogunovicFreerk G. VenhuizenSophie KlimschaStefanos ApostolopoulosAlireza Bab-HadiasharUlas BagciMirza Faisal BegLoza BekaloQiang ChenCarlos CillerKarthik GopinathAmirali K. GostarKiwan JeonZexuan JiSung Ho KangDara D. KoozekananiDonghuan LuDustin MorleyKeshab K. ParhiHyoung Suk ParkAbdolreza RashnoMarinko SarunicSaad ShaikhJayanthi SivaswamyRuwan B. TennakoonShivin YadavSandro De ZanetSebastian M. WaldsteinBianca S. GerendasCaroline KlaverClara I. SánchezUrsula Schmidt-ErfurthPublished in: IEEE Trans. Medical Imaging (2019)
Keyphrases
- optical coherence tomography
- oct images
- fundus images
- retinal images
- vessel detection
- multi directional
- berkeley segmentation dataset
- optic disc
- boundary detection
- medical images
- matched filters
- imaging modalities
- quantitative evaluation
- reliable detection
- image segmentation
- object detection
- automatic detection
- level set
- false positives
- image analysis
- blood vessels
- detection rate
- detection method
- diabetic retinopathy
- vessel segmentation
- landmark detection
- segmentation method
- object segmentation
- medical imaging
- automated segmentation
- energy function
- coronary artery
- segmentation algorithm
- fully automatic
- region growing
- multiple objects