This dataset was created for the MARIO challenge, held as a satellite event of the MICCAI 2024 conference.
Data managers : Gwenole Quellec , Rachid Zeghlache
https://zenodo.org/records/15270469
Famille: Publication
Image-Based Prediction of Retinal Disease Progression
MICCAI Challenges, DIAMOND 2024 and MARIO 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings
Editors: Gwenole Quellec, Mostafa El Habib Daho, Rachid Zeghlache
L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction
R. Zeghlache et al.
Computers in Biology and Medicine 2025; 185:109508
“Spatially resolved imaging of human macular capillaries using adaptive optics-enhanced optical coherence tomography angiography”
Bonnin S and al.
Sci Rep. 2024 Jul 5;14(1):15540. PMID: 38969668; PMCID: PMC11226425
“A review of deep learning-based information fusion techniques for multimodal medical image classification”
Y. Li and al.
Computers in Biology and Medicine,Volume 177, July 2024,108635,ISSN 0010-4825,
https://doi.org/10.1016/j.compbiomed.2024.108635
https://www.sciencedirect.com/science/article/pii/S0010482524007200
“DISCOVER: 2-D multiview summarization of Optical Coherence Tomography Angiography for automatic diabetic retinopathy diagnosis”
M. El Habib Daho and al.
Artificial Intelligence in Medicine, Volume 149,2024,102803,
https://doi.org/10.1016/j.artmed.2024.102803
https://www.sciencedirect.com/science/article/pii/S0933365724000459
