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

Sampath, K and Hareesha, K S and Shetty, Sowjanya (2019) Validation of modified feature-based 3D modeling of scoliotic spine. Cogent Engineering, 6 (1). pp. 1-12. ISSN 2331-1916

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Abstract

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 2̊ . The modified feature based 3D modeling allows for true 3D pre-operative planning which helps the doctor for better treatment with much less time

Item Type: Article
Uncontrolled Keywords: Scoliosis; stereo-radiographic reconstruction; feature-based modeling
Subjects: Engineering > MIT Manipal > Electronics and Communication
Engineering > MIT Manipal > MCA
Depositing User: MIT Library
Date Deposited: 03 Jul 2019 03:57
Last Modified: 03 Jul 2019 06:11
URI: http://eprints.manipal.edu/id/eprint/154072

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