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3D spine shape estimation from single 2D DXA

Abstract:
Scoliosis is currently assessed solely on 2D lateral deviations, but recent studies have also revealed the importance of other imaging planes in understanding the deformation of the spine. Consequently, extracting the spinal geometry in 3D would help quantify these spinal deformations and aid diagnosis. In this study, we propose an automated general framework to estimate the 3D spine shape from 2D DXA scans. We achieve this by explicitly predicting the sagittal view of the spine from the DXA scan. Using these two orthogonal projections of the spine (coronal in DXA, and sagittal from the prediction), we are able to describe the 3D shape of the spine. The prediction is learnt from over 30k paired images of DXA and MRI scans. We assess the performance of the method on a held out test set, and achieve high accuracy (Our code is available at https://www.robots.ox.ac.uk/~vgg/research/dxa-to-3d/index.html).
Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1007/978-3-031-72086-4_1

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
ORCID:
0000-0002-5270-6836
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0002-8945-8573


More from this funder
Funder identifier:
https://ror.org/0439y7842
Grant:
EP/T028572/1


Publisher:
Springer
Host title:
Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 27th International Conference, Marrakesh, Morocco, October 6–10, 2024, Proceedings, Part V
Pages:
3-13
Series:
Lecture Notes in Computer Science
Series number:
15005
Publication date:
2024-10-04
Acceptance date:
2024-09-18
Event title:
27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024)
Event location:
Marrakesh, Morocco
Event website:
https://conferences.miccai.org/2024/
Event start date:
2024-10-06
Event end date:
2024-10-10
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
EISBN:
9783031720864
ISBN:
9783031720857


Language:
English
Keywords:
Pubs id:
2081002
Local pid:
pubs:2081002
Deposit date:
2025-01-28

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