activity
20172025
most cited3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs

8 citations · 18 across the 11 of their papers we have counts for

collaborators

12 papers

eess.IV2025

A graph neural network-based multispectral-view learning model for diabetic macular ischemia detection from color fundus photographs

Qinghua He, Hongyang Jiang, Danqi Fang +7

Diabetic macular ischemia (DMI), marked by the loss of retinal capillaries in the macular area, contributes to vision impairment in patients with diabetes. Although color fundus ph…

cs.CV2024

Forecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT

Arunava Chakravarty, Taha Emre, Dmitrii Lachinov +8

Predicting future disease progression risk from medical images is challenging due to patient heterogeneity, and subtle or unknown imaging biomarkers. Moreover, deep learning (DL) m…

cs.AI2024

Specialized curricula for training vision-language models in retinal image analysis

Robbie Holland, Thomas R. P. Taylor, Christopher Holmes +13

Clinicians spend a significant amount of time reviewing medical images and transcribing their findings regarding patient diagnosis, referral and treatment in text form. Vision-lang…

eess.IV2024

Deep-learning-based clustering of OCT images for biomarker discovery in age-related macular degeneration (Pinnacle study report 4)

Robbie Holland, Rebecca Kaye, Ahmed M. Hagag +9

Diseases are currently managed by grading systems, where patients are stratified by grading systems into stages that indicate patient risk and guide clinical management. However, t…

cs.CV2024

Spatiotemporal Representation Learning for Short and Long Medical Image Time Series

Chengzhi Shen, Martin J. Menten, Hrvoje Bogunović +7

Analyzing temporal developments is crucial for the accurate prognosis of many medical conditions. Temporal changes that occur over short time scales are key to assessing the health…

cs.CV2023★ 8 cited

3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs

Taha Emre, Arunava Chakravarty, Antoine Rivail +10

Self-supervised learning (SSL) has emerged as a powerful technique for improving the efficiency and effectiveness of deep learning models. Contrastive methods are a prominent famil…