1.1k citations · 2.7k across the 50 of their papers we have counts for
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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…
Grow-Push-Prune: aligning deep discriminants for effective structural network compression
Qing Tian, Tal Arbel, James J. Clark
Most of today's popular deep architectures are hand-engineered to be generalists. However, this design procedure usually leads to massive redundant, useless, or even harmful featur…
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…