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Context-aware transformers for spinal cancer detection and radiological grading

Abstract:

This paper proposes a novel transformer-based model architecture for medical imaging problems involving analysis of vertebrae. It considers two applications of such models in MR images: (a) detection of spinal metastases and the related conditions of vertebral fractures and metastatic cord compression, (b) radiological grading of common degenerative changes in intervertebral discs. Our contributions are as follows: (i) We propose a Spinal Context Transformer (SCT), a deep-learning architectur...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-031-16437-8_26

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-8945-8573
Publisher:
Springer Publisher's website
Volume:
13433
Pages:
271–281
Series:
Lecture Notes in Computer Science
Host title:
Proceedings of the 25th International Medical Image Computing and Computer Assisted Intervention (MICCAI 2022)
Publication date:
2022-09-16
Acceptance date:
2022-05-05
Event title:
25th International Medical Image Computing and Computer Assisted Intervention (MICCAI 2022)
Event location:
Singapore
Event website:
https://conferences.miccai.org/2022/
Event start date:
2022-09-18T00:00:00Z
Event end date:
2022-09-22T00:00:00Z
DOI:
EISBN:
978-3-031-16437-8
ISSN:
0302-9743
ISBN:
978-3-031-16436-1
Language:
English
Keywords:
Pubs id:
1272892
Local pid:
pubs:1272892
Deposit date:
2022-08-08

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