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 |
---|---|
其他作者: | de Bruijne, M |
格式: | Conference item |
語言: | English |
出版: |
Springer
2021
|
相似書籍
-
Self-supervised learning for spinal MRIs
由: Jamaludin, A, et al.
出版: (2017) -
A convolutional approach to vertebrae detection and labelling in whole spine MRI
由: Windsor, R, et al.
出版: (2020) -
Vision-language modelling for radiological imaging and reports in the low data regime
由: Windsor, R, et al.
出版: (2024) -
Disentangled Speech Embeddings Using Cross-Modal Self-Supervision
由: Nagrani, A, et al.
出版: (2020) -
Multi-task self-supervised visual learning
由: Doersch, C, et al.
出版: (2017)