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SpineNetV2: Automated detection, labelling and radiological grading of clinical MR scans

Abstract:
This technical report presents SpineNetV2, an automated tool which: (i) detects and labels vertebral bodies in clinical spinal magnetic resonance (MR) scans across a range of commonly used sequences; and (ii) performs radiological grading of lumbar intervertebral discs in T2-weighted scans for a range of common degenerative changes. SpineNetV2 improves over the original SpineNet software in two ways: (1) The vertebral body detection stage is significantly faster, more accurate and works across a range of fields-of-view (as opposed to just lumbar scans). (2) Radiological grading adopts a more powerful architecture, adding several new grading schemes without loss in performance. A demo of the software is available at the project website: http://zeus.robots.ox.ac.uk/spinenet2/
Publication status:
Published
Peer review status:
Reviewed (other)

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Publisher copy:
10.48550/arXiv.2205.01683

Authors

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author


Publisher:
ArXiv
Publication date:
2022-05-03
DOI:


Language:
English
Keywords:
Pubs id:
1272884
Local pid:
pubs:1272884
Deposit date:
2022-08-08
ARK identifier:

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