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Principal deformations modes of articulated models for the analysis of 3D spine deformities

Jonathan Boisvert, Farida Cheriet, Xavier Pennec, Hubert Labelle and Nicholas Ayache

Article (2008)

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Abstract

Articulated models are commonly used for recognition tasks in robotics and in gait analysis, but can also be extremely useful to develop analytical methods targeting spinal deformities studies. The threedimensional analysis of these deformities is critical since they are complex and not restricted to a given plane. Thus, they cannot be assessed as a two-dimensional phenomenon. However, analyzing large databases of 3D spine models is a difficult and time-consuming task. In this context, a method that automatically extracts the most important deformation modes from sets of articulated spine models is proposed. The spine was modeled with two levels of details. In the first level, the global shape of the spine was expressed using a set of rigid transformations that superpose local coordinates systems of neighboring vertebrae. In the second level, anatomical landmarks measured with respect to a vertebra’s local coordinate system were used to quantify vertebra shape. These articulated spine models do not naturally belong to a vector space because of the vertebral rotations. The Fréchet mean, which is a generalization of the conventional mean to Riemannian manifolds, was thus used to compute the mean spine shape. Moreover, a generalized covariance computed in the tangent space of the Fréchet mean was used to construct a statistical shape model of the scoliotic spine. The principal deformation modes were then extracted by performing a principal component analysis (PCA) on the generalized covariance matrix. The principal deformations modes were computed for a large database of untreated scoliotic patients. The obtained results indicate that combining rotation, translation and local vertebra shape into a unified framework leads to an effective and meaningful analysis method for articulated anatomical structures. The computed deformation modes also revealed clinically relevant information. For instance, the first mode of deformation is associated with patients’ growth, the second is a double thoraco-lumbar curve and the third is a thoracic curve. Other experiments were performed on patients classified by orthopedists with respect to a widely used two-dimensional surgical planning system (the Lenke classification) and patterns relevant to the definition of a new three-dimensional classification were identified. Finally, relationships between local vertebrae shapes and global spine shape (such as vertebra wedging) were demonstrated using a sample of 3D spine reconstructions with 14 anatomical landmarks per vertebra.

Uncontrolled Keywords

shape analysis; articulated models; spinal deformities; scoliosis; 3D reconstruction; surgical classifications

Subjects: 1900 Biomedical engineering > 1900 Biomedical engineering
1900 Biomedical engineering > 1901 Biomedical technology
1900 Biomedical engineering > 1903 Biomechanics
2700 Information technology > 2706 Software engineering
2700 Information technology > 2708 Image and video processing
2700 Information technology > 2717 Modelling and simulation studies
Department: Department of Computer Engineering and Software Engineering
Funders: CRSNG / NSERC, Fonds de recherche du Québec - Nature et technologies (FRQNT), Canadian Institutes of Health Research (CIHR)
PolyPublie URL: https://publications.polymtl.ca/55810/
Journal Title: ELCVIA - Electronic Letters on Computer Vision and Image Analysis (vol. 7, no. 4)
Publisher: Universitat Autonoma de Barcelona
DOI: 10.5565/rev/elcvia.165
Official URL: https://doi.org/10.5565/rev/elcvia.165
Date Deposited: 02 Oct 2023 15:11
Last Modified: 05 Apr 2024 23:11
Cite in APA 7: Boisvert, J., Cheriet, F., Pennec, X., Labelle, H., & Ayache, N. (2008). Principal deformations modes of articulated models for the analysis of 3D spine deformities. ELCVIA - Electronic Letters on Computer Vision and Image Analysis, 7(4), 13-31. https://doi.org/10.5565/rev/elcvia.165

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