107 citations · 494 across the 48 of their papers we have counts for
6 papers · 2 filters
Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models
Mischa Dombrowski, Hadrien Reynaud, Matthew Baugh +1
Curating datasets for object segmentation is a difficult task. With the advent of large-scale pre-trained generative models, conditional image generation has been given a significa…
Self-Supervised 3D Human Pose Estimation in Static Video Via Neural Rendering
Luca Schmidtke, Benjamin Hou, Athanasios Vlontzos +1
Inferring 3D human pose from 2D images is a challenging and long-standing problem in the field of computer vision with many applications including motion capture, virtual reality,…
Improved post-hoc probability calibration for out-of-domain MRI segmentation
Cheng Ouyang, Shuo Wang, Chen Chen +4
Probability calibration for deep models is highly desirable in safety-critical applications such as medical imaging. It makes output probabilities of deep networks interpretable, b…
nnOOD: A Framework for Benchmarking Self-supervised Anomaly Localisation Methods
Matthew Baugh, Jeremy Tan, Athanasios Vlontzos +2
The wide variety of in-distribution and out-of-distribution data in medical imaging makes universal anomaly detection a challenging task. Recently a number of self-supervised metho…
D'ARTAGNAN: Counterfactual Video Generation
Hadrien Reynaud, Athanasios Vlontzos, Mischa Dombrowski +4
Causally-enabled machine learning frameworks could help clinicians to identify the best course of treatments by answering counterfactual questions. We explore this path for the cas…
A Review of Causality for Learning Algorithms in Medical Image Analysis
Athanasios Vlontzos, Daniel Rueckert, Bernhard Kainz
Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machi…