Borges, Pedro;
Shaw, Richard;
Varsavsky, Thomas;
Kläser, Kerstin;
Thomas, David;
Drobnjak, Ivana;
Ourselin, Sebastien;
(2024)
Acquisition-invariant brain MRI segmentation with informative uncertainties.
Medical Image Analysis
, 92
, Article 103058. 10.1016/j.media.2023.103058.
Text
MIA___Revision_Three___Clean.pdf - Accepted Version Access restricted to UCL open access staff until 8 December 2025. Download (2MB) |
Abstract
Combining multi-site data can strengthen and uncover trends, but is a task that is marred by the influence of site-specific covariates that can bias the data and, therefore, any downstream analyses. Post-hoc multi-site correction methods exist but have strong assumptions that often do not hold in real-world scenarios. Algorithms should be designed in a way that can account for site-specific effects, such as those that arise from sequence parameter choices, and in instances where generalisation fails, should be able to identify such a failure by means of explicit uncertainty modelling. This body of work showcases such an algorithm that can become robust to the physics of acquisition in the context of segmentation tasks while simultaneously modelling uncertainty. We demonstrate that our method not only generalises to complete holdout datasets, preserving segmentation quality but does so while also accounting for site-specific sequence choices, which also allows it to perform as a harmonisation tool.
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