14 citations · 33 across the 36 of their papers we have counts for
8 papers · 1 filter
Pitfalls of topology-aware image segmentation
Alexander H. Berger, Laurin Lux, Alexander Weers +3
Topological correctness, i.e., the preservation of structural integrity and specific characteristics of shape, is a fundamental requirement for medical imaging tasks, such as neuro…
Interpretable deformable image registration: A geometric deep learning perspective
Vasiliki Sideri-Lampretsa, Nil Stolt-Ansó, Huaqi Qiu +4
Deformable image registration poses a challenging problem where, unlike most deep learning tasks, a complex relationship between multiple coordinate systems has to be considered. A…
OTIS: Learning High-Quality Time Series Features With Tiny Encoders
Özgün Turgut, Philip Müller, Martin J. Menten +1
We introduce OTIS, an open time series encoder that yields high-quality time series features for downstream deployment on any system, including resource-constrained wearables and i…
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…
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…
Diff-Def: Diffusion-Generated Deformation Fields for Conditional Atlases
Sophie Starck, Vasiliki Sideri-Lampretsa, Bernhard Kainz +3
Anatomical atlases are widely used for population studies and analysis. Conditional atlases target a specific sub-population defined via certain conditions, such as demographics or…
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…
Cross-domain and Cross-dimension Learning for Image-to-Graph Transformers
Alexander H. Berger, Laurin Lux, Suprosanna Shit +5
Direct image-to-graph transformation is a challenging task that involves solving object detection and relationship prediction in a single model. Due to this task's complexity, larg…