26 citations · 27 across the 4 of their papers we have counts for
5 papers · 1 filter
SD-RetinaNet: Topologically Constrained Semi-Supervised Retinal Lesion and Layer Segmentation in OCT
Botond Fazekas, Guilherme Aresta, Philipp Seeböck +3
Optical coherence tomography (OCT) is widely used for diagnosing and monitoring retinal diseases, such as age-related macular degeneration (AMD). The segmentation of biomarkers suc…
RetFiner: A Vision-Language Refinement Scheme for Retinal Foundation Models
Ronald Fecso, José Morano, Ursula Schmidt-Erfurth +1
The rise of imaging techniques such as optical coherence tomography (OCT) and advances in deep learning (DL) have enabled clinicians and researchers to streamline retinal disease s…
MIRAGE: Multimodal foundation model and benchmark for comprehensive retinal OCT image analysis
José Morano, Botond Fazekas, Emese Sükei +7
Artificial intelligence (AI) has become a fundamental tool for assisting clinicians in analyzing ophthalmic images, such as optical coherence tomography (OCT). However, developing…
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…
Learning Spatio-Temporal Model of Disease Progression with NeuralODEs from Longitudinal Volumetric Data
Dmitrii Lachinov, Arunava Chakravarty, Christoph Grechenig +2
Robust forecasting of the future anatomical changes inflicted by an ongoing disease is an extremely challenging task that is out of grasp even for experienced healthcare profession…