Validation of modified feature-based 3D modeling of scoliotic spine

Three out of every 100 people in this world have some form of scoliosis. A doctor would suggest surgery if scoliosis is severe in certain conditions to prevent it from getting worse. The deformity of spine can be visualized well in 3D rather than in 2D as it is time-consuming to evaluate the degree...

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Autores principales: Sampath Kumar, Hareesh KS, Soujanya Shetty
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Lenguaje:EN
Publicado: Taylor & Francis Group 2019
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Acceso en línea:https://doaj.org/article/fc1265c7af4d44078852a5dc885dc882
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spelling oai:doaj.org-article:fc1265c7af4d44078852a5dc885dc8822021-11-04T15:51:56ZValidation of modified feature-based 3D modeling of scoliotic spine2331-191610.1080/23311916.2019.1623854https://doaj.org/article/fc1265c7af4d44078852a5dc885dc8822019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2019.1623854https://doaj.org/toc/2331-1916Three out of every 100 people in this world have some form of scoliosis. A doctor would suggest surgery if scoliosis is severe in certain conditions to prevent it from getting worse. The deformity of spine can be visualized well in 3D rather than in 2D as it is time-consuming to evaluate the degree of deformity. CATIA V5 is used to develop feature-based modeling. The angles of vertebrae orientation from biplanar X-rays are fed into the CATIA interface which forms the orientation of the 3D spine model. The feature-based model is modified using the morpho-realistic model for increasing the accuracy. The validation procedure for the feature-based model is divided into quantitative and qualitative analysis. In quantitative analysis, the One Sided Hausdorff Distance (OSHD), Average Surface Distance (ASD), Cobb angle and Axial Vertebral Rotation (AVR) metrics are obtained for inter-observer variability and intra-observer variability. In qualitative analysis, the model is projected along the frontal and lateral radiographs and compared with reference radiographs. The accuracy of the model can be estimated by the uncertainty in these parameters. The mean surface model reconstruction errors were found to be smaller than 1.5 mm in comparing cadaver Computed Tomography (CT) scan as well as for the 10 cases including inter-observer and intra-observer variability. The average differences for AVR and Cobb angle were less than 2 ̊. The modified feature-based 3D modeling allows for true 3D pre-operative planning which helps the doctor for better treatment with much less time.Sampath KumarHareesh KSSoujanya ShettyTaylor & Francis Grouparticlescoliosisstereo-radiographic reconstructionfeature-based modelingEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 6, Iss 1 (2019)
institution DOAJ
collection DOAJ
language EN
topic scoliosis
stereo-radiographic reconstruction
feature-based modeling
Engineering (General). Civil engineering (General)
TA1-2040
spellingShingle scoliosis
stereo-radiographic reconstruction
feature-based modeling
Engineering (General). Civil engineering (General)
TA1-2040
Sampath Kumar
Hareesh KS
Soujanya Shetty
Validation of modified feature-based 3D modeling of scoliotic spine
description Three out of every 100 people in this world have some form of scoliosis. A doctor would suggest surgery if scoliosis is severe in certain conditions to prevent it from getting worse. The deformity of spine can be visualized well in 3D rather than in 2D as it is time-consuming to evaluate the degree of deformity. CATIA V5 is used to develop feature-based modeling. The angles of vertebrae orientation from biplanar X-rays are fed into the CATIA interface which forms the orientation of the 3D spine model. The feature-based model is modified using the morpho-realistic model for increasing the accuracy. The validation procedure for the feature-based model is divided into quantitative and qualitative analysis. In quantitative analysis, the One Sided Hausdorff Distance (OSHD), Average Surface Distance (ASD), Cobb angle and Axial Vertebral Rotation (AVR) metrics are obtained for inter-observer variability and intra-observer variability. In qualitative analysis, the model is projected along the frontal and lateral radiographs and compared with reference radiographs. The accuracy of the model can be estimated by the uncertainty in these parameters. The mean surface model reconstruction errors were found to be smaller than 1.5 mm in comparing cadaver Computed Tomography (CT) scan as well as for the 10 cases including inter-observer and intra-observer variability. The average differences for AVR and Cobb angle were less than 2 ̊. The modified feature-based 3D modeling allows for true 3D pre-operative planning which helps the doctor for better treatment with much less time.
format article
author Sampath Kumar
Hareesh KS
Soujanya Shetty
author_facet Sampath Kumar
Hareesh KS
Soujanya Shetty
author_sort Sampath Kumar
title Validation of modified feature-based 3D modeling of scoliotic spine
title_short Validation of modified feature-based 3D modeling of scoliotic spine
title_full Validation of modified feature-based 3D modeling of scoliotic spine
title_fullStr Validation of modified feature-based 3D modeling of scoliotic spine
title_full_unstemmed Validation of modified feature-based 3D modeling of scoliotic spine
title_sort validation of modified feature-based 3d modeling of scoliotic spine
publisher Taylor & Francis Group
publishDate 2019
url https://doaj.org/article/fc1265c7af4d44078852a5dc885dc882
work_keys_str_mv AT sampathkumar validationofmodifiedfeaturebased3dmodelingofscolioticspine
AT hareeshks validationofmodifiedfeaturebased3dmodelingofscolioticspine
AT soujanyashetty validationofmodifiedfeaturebased3dmodelingofscolioticspine
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