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A statistical shape model of the human second cervical vertebra

Clogenson, Marine ; Duff, John ; Luethi, Marcel ; Levivier, Marc ; Meuli, Reto ; Baur, Charles ; Henein, Simon

In: International Journal of Computer Assisted Radiology and Surgery, 2015, vol. 10, no. 7, p. 1097-1107

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    Titre
    • A statistical shape model of the human second cervical vertebra
    Auteur
    • Clogenson, Marine. École Polytechnique Fédérale de Lausanne, Instant-Lab, Rue de la Maladière 71b, 2000, Neuchâtel, Switzerland
    • Duff, John. Neurochirurgie, Centre Hospitalier Universitaire Vaudois et Université de Lausanne, Rue de Bugnon 46, 1011, Lausanne, Switzerland
    • Luethi, Marcel. Computer Science Department, University of Basel, Bernoullistrasse 16, 4056, Basel, Switzerland
    • Levivier, Marc. Neurochirurgie, Centre Hospitalier Universitaire Vaudois et Université de Lausanne, Rue de Bugnon 46, 1011, Lausanne, Switzerland
    • Meuli, Reto. Service de radiodiagnostic et radiologie interventionnelle, Centre Hospitalier Universitaire Vaudois et Université de Lausanne, Rue de Bugnon 46, 1011, Lausanne, Switzerland
    • Baur, Charles. École Polytechnique Fédérale de Lausanne, Instant-Lab, Rue de la Maladière 71b, 2000, Neuchâtel, Switzerland
    • Henein, Simon. École Polytechnique Fédérale de Lausanne, Instant-Lab, Rue de la Maladière 71b, 2000, Neuchâtel, Switzerland
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • International Journal of Computer Assisted Radiology and Surgery, 2015, vol. 10, no. 7, p. 1097-1107. Springer Berlin Heidelberg
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:332116
    Summary
    Purpose : Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. Methods : The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. Results : The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. Conclusion : The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.