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Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework
Different pathologies of the vertebral column, such as scoliosis, require quantification of the mobility of individual vertebrae or of curves of the spine for treatment planning. Without the necessary mobility, vertebrae can not be safely re-positioned and fused. The current clinical workflow consis...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279937/ http://dx.doi.org/10.1007/978-3-030-50120-4_7 |
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author | Drobny, David Ranzini, Marta Isaac, Amanda Vercauteren, Tom Ourselin, Sébastien Choi, David Modat, Marc |
author_facet | Drobny, David Ranzini, Marta Isaac, Amanda Vercauteren, Tom Ourselin, Sébastien Choi, David Modat, Marc |
author_sort | Drobny, David |
collection | PubMed |
description | Different pathologies of the vertebral column, such as scoliosis, require quantification of the mobility of individual vertebrae or of curves of the spine for treatment planning. Without the necessary mobility, vertebrae can not be safely re-positioned and fused. The current clinical workflow consists of radiologists or surgeons estimating angular differences of neighbouring vertebrae from different x-ray images. This procedure is time consuming and prone to inaccuracy. The proposed method automates this quantification by deforming a CT image in a physiologically reasonable way and matching it to the x-ray images of interest. We propose a proof of concept evaluation on synthetic data. The automatic and quantitative analysis enables reproducible results independent of the investigator. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this chapter (10.1007/978-3-030-50120-4_7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-7279937 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72799372020-06-09 Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework Drobny, David Ranzini, Marta Isaac, Amanda Vercauteren, Tom Ourselin, Sébastien Choi, David Modat, Marc Biomedical Image Registration Article Different pathologies of the vertebral column, such as scoliosis, require quantification of the mobility of individual vertebrae or of curves of the spine for treatment planning. Without the necessary mobility, vertebrae can not be safely re-positioned and fused. The current clinical workflow consists of radiologists or surgeons estimating angular differences of neighbouring vertebrae from different x-ray images. This procedure is time consuming and prone to inaccuracy. The proposed method automates this quantification by deforming a CT image in a physiologically reasonable way and matching it to the x-ray images of interest. We propose a proof of concept evaluation on synthetic data. The automatic and quantitative analysis enables reproducible results independent of the investigator. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this chapter (10.1007/978-3-030-50120-4_7) contains supplementary material, which is available to authorized users. 2020-05-13 /pmc/articles/PMC7279937/ http://dx.doi.org/10.1007/978-3-030-50120-4_7 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Drobny, David Ranzini, Marta Isaac, Amanda Vercauteren, Tom Ourselin, Sébastien Choi, David Modat, Marc Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework |
title | Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework |
title_full | Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework |
title_fullStr | Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework |
title_full_unstemmed | Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework |
title_short | Towards Automated Spine Mobility Quantification: A Locally Rigid CT to X-ray Registration Framework |
title_sort | towards automated spine mobility quantification: a locally rigid ct to x-ray registration framework |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279937/ http://dx.doi.org/10.1007/978-3-030-50120-4_7 |
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