21 citations · 36 across the 9 of their papers we have counts for
3 papers · 1 filter
FedHarmony: Unlearning Scanner Bias with Distributed Data
Nicola K Dinsdale, Mark Jenkinson, Ana IL Namburete
The ability to combine data across scanners and studies is vital for neuroimaging, to increase both statistical power and the representation of biological variability. However, com…
Uncertainty categories in medical image segmentation: a study of source-related diversity
Luke Whitbread, Mark Jenkinson
Measuring uncertainties in the output of a deep learning method is useful in several ways, such as in assisting with interpretation of the outputs, helping build confidence with en…
Mutual information neural estimation for unsupervised multi-modal registration of brain images
Gerard Snaauw, Michele Sasdelli, Gabriel Maicas +4
Many applications in image-guided surgery and therapy require fast and reliable non-linear, multi-modal image registration. Recently proposed unsupervised deep learning-based regis…