80 citations · 148 across the 24 of their papers we have counts for
11 papers · 1 filter
Automatic detection and prediction of nAMD activity change in retinal OCT using Siamese networks and Wasserstein Distance for ordinality
Taha Emre, Teresa Araújo, Marzieh Oghbaie +3
Neovascular age-related macular degeneration (nAMD) is a leading cause of vision loss among older adults, where disease activity detection and progression prediction are critical f…
Comparative Analysis of Data Augmentation for Retinal OCT Biomarker Segmentation
Markus Unterdechler, Botond Fazekas, Guilherme Aresta +1
Data augmentation plays a crucial role in addressing the challenge of limited expert-annotated datasets in deep learning applications for retinal Optical Coherence Tomography (OCT)…
RRWNet: Recursive Refinement Network for effective retinal artery/vein segmentation and classification
José Morano, Guilherme Aresta, Hrvoje Bogunović
The caliber and configuration of retinal blood vessels serve as important biomarkers for various diseases and medical conditions. A thorough analysis of the retinal vasculature req…
SAMedOCT: Adapting Segment Anything Model (SAM) for Retinal OCT
Botond Fazekas, José Morano, Dmitrii Lachinov +2
The Segment Anything Model (SAM) has gained significant attention in the field of image segmentation due to its impressive capabilities and prompt-based interface. While SAM has al…
Self-supervised learning via inter-modal reconstruction and feature projection networks for label-efficient 3D-to-2D segmentation
José Morano, Guilherme Aresta, Dmitrii Lachinov +3
Deep learning has become a valuable tool for the automation of certain medical image segmentation tasks, significantly relieving the workload of medical specialists. Some of these…
PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation
Huihui Fang, Fei Li, Junde Wu +6
Pathologic myopia (PM) is a common blinding retinal degeneration suffered by highly myopic population. Early screening of this condition can reduce the damage caused by the associa…
Morph-SSL: Self-Supervision with Longitudinal Morphing to Predict AMD Progression from OCT
Arunava Chakravarty, Taha Emre, Oliver Leingang +8
The lack of reliable biomarkers makes predicting the conversion from intermediate to neovascular age-related macular degeneration (iAMD, nAMD) a challenging task. We develop a Deep…
AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge
Coen de Vente, Koenraad A. Vermeer, Nicolas Jaccard +33
The early detection of glaucoma is essential in preventing visual impairment. Artificial intelligence (AI) can be used to analyze color fundus photographs (CFPs) in a cost-effectiv…
Clustering disease trajectories in contrastive feature space for biomarker discovery in age-related macular degeneration
Robbie Holland, Oliver Leingang, Christopher Holmes +13
Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. Current grading systems based on imaging biomarkers only coarsely group disease stages into…
REFUGE2 Challenge: A Treasure Trove for Multi-Dimension Analysis and Evaluation in Glaucoma Screening
Huihui Fang, Fei Li, Junde Wu +25
With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there ar…
ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images
Huihui Fang, Fei Li, Huazhu Fu +28
Age-related macular degeneration (AMD) is the leading cause of visual impairment among elderly in the world. Early detection of AMD is of great importance, as the vision loss cause…