430 citations · 722 across the 13 of their papers we have counts for
6 papers · 1 filter
Causality matters in medical imaging
Daniel C. Castro, Ian Walker, Ben Glocker
This article discusses how the language of causality can shed new light on the major challenges in machine learning for medical imaging: 1) data scarcity, which is the limited avai…
Domain Generalization via Model-Agnostic Learning of Semantic Features
Qi Dou, Daniel C. Castro, Konstantinos Kamnitsas +1
Generalization capability to unseen domains is crucial for machine learning models when deploying to real-world conditions. We investigate the challenging problem of domain general…
Vertebrae Detection and Localization in CT with Two-Stage CNNs and Dense Annotations
James McCouat, Ben Glocker
We propose a new, two-stage approach to the vertebrae centroid detection and localization problem. The first stage detects where the vertebrae appear in the scan using 3D samples,…
Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects
Ben Glocker, Robert Robinson, Daniel C. Castro +2
This is an empirical study to investigate the impact of scanner effects when using machine learning on multi-site neuroimaging data. We utilize structural T1-weighted brain MRI obt…
Needles in Haystacks: On Classifying Tiny Objects in Large Images
Nick Pawlowski, Suvrat Bhooshan, Nicolas Ballas +3
In some important computer vision domains, such as medical or hyperspectral imaging, we care about the classification of tiny objects in large images. However, most Convolutional N…
Medical Imaging with Deep Learning: MIDL 2019 -- Extended Abstract Track
M. Jorge Cardoso, Aasa Feragen, Ben Glocker +4
This compendium gathers all the accepted extended abstracts from the Second International Conference on Medical Imaging with Deep Learning (MIDL 2019), held in London, UK, 8-10 Jul…