Self-supervised multi-modal alignment for whole body medical imaging
This paper explores the use of self-supervised deep learning in medical imaging in cases where two scan modalities are available for the same subject. Specifically, we use a large publicly-available dataset of over 20,000 subjects from the UK Biobank with both whole body Dixon technique magnetic res...
Main Authors: | Windsor, R, Jamaludin, A, Kadir, T, Zisserman, A |
---|---|
Andre forfattere: | de Bruijne, M |
Format: | Conference item |
Sprog: | English |
Udgivet: |
Springer
2021
|
Lignende værker
-
Self-supervised learning for spinal MRIs
af: Jamaludin, A, et al.
Udgivet: (2017) -
A convolutional approach to vertebrae detection and labelling in whole spine MRI
af: Windsor, R, et al.
Udgivet: (2020) -
Vision-language modelling for radiological imaging and reports in the low data regime
af: Windsor, R, et al.
Udgivet: (2024) -
Disentangled Speech Embeddings Using Cross-Modal Self-Supervision
af: Nagrani, A, et al.
Udgivet: (2020) -
Multi-task self-supervised visual learning
af: Doersch, C, et al.
Udgivet: (2017)