Cargando…
A Semi-Automatic Algorithm for Estimating Cobb Angle
BACKGROUND: Scoliosis is the most common type of spinal deformity. A universal and standard method for evaluating scoliosis is Cobb angle measurement, but several studies have shown that there is intra- and inter- observer variation in measuring cobb angle manually. OBJECTIVE: Develop a computer- as...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Journal of Biomedical Physics and Engineering
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613161/ https://www.ncbi.nlm.nih.gov/pubmed/31341877 http://dx.doi.org/10.31661/jbpe.v9i3Jun.730 |
_version_ | 1783433005601128448 |
---|---|
author | A., Safari H., Parsaei A., Zamani B., Pourabbas |
author_facet | A., Safari H., Parsaei A., Zamani B., Pourabbas |
author_sort | A., Safari |
collection | PubMed |
description | BACKGROUND: Scoliosis is the most common type of spinal deformity. A universal and standard method for evaluating scoliosis is Cobb angle measurement, but several studies have shown that there is intra- and inter- observer variation in measuring cobb angle manually. OBJECTIVE: Develop a computer- assisted system to decrease operator-dependent errors in Cobb angle measurement. METHODS: The spinal cord in the given x-ray image of the spine is highlighted using contract-stretching technique. The overall structural curvature of the spine is determined by a semi-automatic algorithm aided by the operator. Once the morphologic curve of the spine is determined, in the last step the cobb-angle is estimated by calculating the angle between two normal lines to the spinal curve at the inflection points of the curve. RESULTS: Evaluation results of the developed algorithms using 14 radiographs of patients ( 4 - 40 years old) with cobb angle ranges from 34 - 82 degrees, revealed that the developed algorithm accurately estimated cobb angle. Statistical analysis showed that average angle values estimated using the developed method and that provided by experts are statistically equal. The correlation coefficient between the angle values estimated using the developed algorithm and those provided by the expert is 0.81. CONCLUSION: Compared with previous algorithms, the developed system is easy to use, less operator-dependent, accurate, and reliable. The obtained results are promising and show that the developed computer-based system could be used to quantify scoliosis by measuring Cobb angle. |
format | Online Article Text |
id | pubmed-6613161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Journal of Biomedical Physics and Engineering |
record_format | MEDLINE/PubMed |
spelling | pubmed-66131612019-07-24 A Semi-Automatic Algorithm for Estimating Cobb Angle A., Safari H., Parsaei A., Zamani B., Pourabbas J Biomed Phys Eng Original Article BACKGROUND: Scoliosis is the most common type of spinal deformity. A universal and standard method for evaluating scoliosis is Cobb angle measurement, but several studies have shown that there is intra- and inter- observer variation in measuring cobb angle manually. OBJECTIVE: Develop a computer- assisted system to decrease operator-dependent errors in Cobb angle measurement. METHODS: The spinal cord in the given x-ray image of the spine is highlighted using contract-stretching technique. The overall structural curvature of the spine is determined by a semi-automatic algorithm aided by the operator. Once the morphologic curve of the spine is determined, in the last step the cobb-angle is estimated by calculating the angle between two normal lines to the spinal curve at the inflection points of the curve. RESULTS: Evaluation results of the developed algorithms using 14 radiographs of patients ( 4 - 40 years old) with cobb angle ranges from 34 - 82 degrees, revealed that the developed algorithm accurately estimated cobb angle. Statistical analysis showed that average angle values estimated using the developed method and that provided by experts are statistically equal. The correlation coefficient between the angle values estimated using the developed algorithm and those provided by the expert is 0.81. CONCLUSION: Compared with previous algorithms, the developed system is easy to use, less operator-dependent, accurate, and reliable. The obtained results are promising and show that the developed computer-based system could be used to quantify scoliosis by measuring Cobb angle. Journal of Biomedical Physics and Engineering 2019-06-01 /pmc/articles/PMC6613161/ /pubmed/31341877 http://dx.doi.org/10.31661/jbpe.v9i3Jun.730 Text en Copyright: © Journal of Biomedical Physics and Engineering http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article A., Safari H., Parsaei A., Zamani B., Pourabbas A Semi-Automatic Algorithm for Estimating Cobb Angle |
title | A Semi-Automatic Algorithm for Estimating Cobb Angle
|
title_full | A Semi-Automatic Algorithm for Estimating Cobb Angle
|
title_fullStr | A Semi-Automatic Algorithm for Estimating Cobb Angle
|
title_full_unstemmed | A Semi-Automatic Algorithm for Estimating Cobb Angle
|
title_short | A Semi-Automatic Algorithm for Estimating Cobb Angle
|
title_sort | semi-automatic algorithm for estimating cobb angle |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6613161/ https://www.ncbi.nlm.nih.gov/pubmed/31341877 http://dx.doi.org/10.31661/jbpe.v9i3Jun.730 |
work_keys_str_mv | AT asafari asemiautomaticalgorithmforestimatingcobbangle AT hparsaei asemiautomaticalgorithmforestimatingcobbangle AT azamani asemiautomaticalgorithmforestimatingcobbangle AT bpourabbas asemiautomaticalgorithmforestimatingcobbangle AT asafari semiautomaticalgorithmforestimatingcobbangle AT hparsaei semiautomaticalgorithmforestimatingcobbangle AT azamani semiautomaticalgorithmforestimatingcobbangle AT bpourabbas semiautomaticalgorithmforestimatingcobbangle |