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Spatio-Temporal Signatures to Predict Retinal Disease Recurrence.

, , , , , , , and . IPMI, volume 9123 of Lecture Notes in Computer Science, page 152-163. Springer, (2015)

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Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data., , , , , , , , and . CoRR, (2018)End-to-End Deep Learning Model for Predicting Treatment Requirements in Neovascular AMD From Longitudinal Retinal OCT Imaging., , and . IEEE J. Biomed. Health Informatics, 24 (12): 3456-3465 (2020)Robust Fovea Detection in Retinal OCT Imaging Using Deep Learning., , , , and . IEEE J. Biomed. Health Informatics, 26 (8): 3927-3937 (2022)U2-Net: A Bayesian U-Net Model With Epistemic Uncertainty Feedback For Photoreceptor Layer Segmentation In Pathological OCT Scans., , , , , , , and . ISBI, page 1441-1445. IEEE, (2019)Deep Learning Prediction Of Age And Sex From Optical Coherence Tomography., , , , , and . ISBI, page 238-242. IEEE, (2021)Spatio-Temporal Signatures to Predict Retinal Disease Recurrence., , , , , , , and . IPMI, volume 9123 of Lecture Notes in Computer Science, page 152-163. Springer, (2015)Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT., , , , , and . MICCAI (1), volume 12901 of Lecture Notes in Computer Science, page 431-441. Springer, (2021)Self-supervised Learning via Inter-modal Reconstruction and Feature Projection Networks for Label-Efficient 3D-to-2D Segmentation., , , , , and . MICCAI (4), volume 14223 of Lecture Notes in Computer Science, page 589-599. Springer, (2023)Clustering Disease Trajectories in Contrastive Feature Space for Biomarker Proposal in Age-Related Macular Degeneration., , , , , , , , , and 5 other author(s). MICCAI (7), volume 14226 of Lecture Notes in Computer Science, page 724-734. Springer, (2023)Pretrained Deep 2.5D Models for Efficient Predictive Modeling from Retinal OCT: A PINNACLE Study Report., , , , , , , , , and 2 other author(s). OMIA@MICCAI, volume 14096 of Lecture Notes in Computer Science, page 132-141. Springer, (2023)