Conference item : Abstract
Deep learning for automated insertion point annotation of CMR T1 maps
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Authors
- Publisher:
- IEEE
- Host title:
- Conference Proceedings ISBI 2024
- Article number:
- 1512
- Publication date:
- 2024-05-27
- Acceptance date:
- 2024-03-18
- Event title:
- 2024 IEEE 21st International Symposium on Biomedical Imaging (ISBI)
- Event series:
- International Symposium on Biomedical Imaging
- Event location:
- Athens, Greece
- Event website:
- https://biomedicalimaging.org/2024/
- Event start date:
- 2024-05-27
- Event end date:
- 2024-05-30
- ISBN:
- 979-8-3503-1333-8
- Language:
-
English
- Subtype:
-
Abstract
- Pubs id:
-
2001147
- Local pid:
-
pubs:2001147
- Deposit date:
-
2024-05-27
Terms of use
- Copyright date:
- 2024
- Notes:
-
This paper was presented at the 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), 27th-30th May 2024, Athens, Greece.
This is the accepted manuscript version of the article. The final version is available online from the publisher.
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