1.1k citations · 1.1k across the 5 of their papers we have counts for
6 papers
Optimization over Random and Gradient Probabilistic Pixel Sampling for Fast, Robust Multi-Resolution Image Registration
Boris N. Oreshkin, Tal Arbel
This paper presents an approach to fast image registration through probabilistic pixel sampling. We propose a practical scheme to leverage the benefits of two state-of-the-art pixe…
Uncertainty driven probabilistic voxel selection for image registration
Boris N. Oreshkin, Tal Arbel
This paper presents a novel probabilistic voxel selection strategy for medical image registration in time-sensitive contexts, where the goal is aggressive voxel sampling (e.g. usin…
Medical Imaging with Deep Learning: MIDL 2020 -- Short Paper Track
Tal Arbel, Ismail Ben Ayed, Marleen de Bruijne +3
This compendium gathers all the accepted extended abstracts from the Third International Conference on Medical Imaging with Deep Learning (MIDL 2020), held in Montreal, Canada, 6-9…
Uncertainty Evaluation Metric for Brain Tumour Segmentation
Raghav Mehta, Angelos Filos, Yarin Gal +1
In this paper, we develop a metric designed to assess and rank uncertainty measures for the task of brain tumour sub-tissue segmentation in the BraTS 2019 sub-challenge on uncertai…
BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier-Hein, Annika Reinke, Michal Kozubek +11
The number of biomedical image analysis challenges organized per year is steadily increasing. These international competitions have the purpose of benchmarking algorithms on common…
Domain-adversarial neural networks to address the appearance variability of histopathology images
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof +2
Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters. The parameters can vary between pathology labs and within the same lab…