Report
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)
Actions
Access Document
- Files:
-
-
(Preview, Pre-print, pdf, 13.6MB, Terms of use)
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- Publisher copy:
- 10.48550/arXiv.2205.01683
Authors
- Publisher:
- ArXiv
- Publication date:
- 2022-05-03
- DOI:
- Language:
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English
- Keywords:
- Pubs id:
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1272884
- Local pid:
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pubs:1272884
- Deposit date:
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2022-08-08
- ARK identifier:
Terms of use
- Copyright holder:
- Windsor et al.
- Copyright date:
- 2022
- Rights statement:
- Copyright © 2022 The Author(s).
- Licence:
- CC Attribution (CC BY)
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