activity
20242026
most citedQUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

5 citations · 5 across the 2 of their papers we have counts for

collaborators

6 papers

cs.LG2026

What Cohort INRs Encode and Where to Freeze Them

Vasiliki Sideri-Lampretsa, Sophie Starck, Robbie Holland +2

Reusing the early layers of cohort-trained INRs as initialization for new signals has been shown to accelerate and improve signal fitting, yet it remains unclear which layers of th…

eess.IV2025

Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method

Daniel Scholz, Ayhan Can Erdur, Robbie Holland +4

Magnetic resonance imaging (MRI) is an invaluable tool for clinical and research applications. Yet, variations in scanners and acquisition parameters cause inconsistencies in image…

cs.CV2025

Parametric shape models for vessels learned from segmentations via differentiable voxelization

Alina F. Dima, Suprosanna Shit, Huaqi Qiu +8

Vessels are complex structures in the body that have been studied extensively in multiple representations. While voxelization is the most common of them, meshes and parametric mode…

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.IV20245 cited

QUBIQ: Uncertainty Quantification for Biomedical Image Segmentation Challenge

Hongwei Bran Li, Fernando Navarro, Ivan Ezhov +77

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a sign…

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…