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Atlas-Based Automatic Generation of Subject-Specific Finite Element Tongue Meshes

  • Computational Biomechanics for Patient-Specific Applications
  • Published:
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Abstract

Generation of subject-specific 3D finite element (FE) models requires the processing of numerous medical images in order to precisely extract geometrical information about subject-specific anatomy. This processing remains extremely challenging. To overcome this difficulty, we present an automatic atlas-based method that generates subject-specific FE meshes via a 3D registration guided by Magnetic Resonance images. The method extracts a 3D transformation by registering the atlas’ volume image to the subject’s one, and establishes a one-to-one correspondence between the two volumes. The 3D transformation field deforms the atlas’ mesh to generate the subject-specific FE mesh. To preserve the quality of the subject-specific mesh, a diffeomorphic non-rigid registration based on B-spline free-form deformations is used, which guarantees a non-folding and one-to-one transformation. Two evaluations of the method are provided. First, a publicly available CT-database is used to assess the capability to accurately capture the complexity of each subject-specific Lung’s geometry. Second, FE tongue meshes are generated for two healthy volunteers and two patients suffering from tongue cancer using MR images. It is shown that the method generates an appropriate representation of the subject-specific geometry while preserving the quality of the FE meshes for subsequent FE analysis. To demonstrate the importance of our method in a clinical context, a subject-specific mesh is used to simulate tongue’s biomechanical response to the activation of an important tongue muscle, before and after cancer surgery.

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Acknowledgments

This work was partly funded by the AGIR program (Grenoble Universities) and by the ANR under reference ANR-11-LABX-0004. We are grateful to Georges Bettega (Grenoble Hospital), Mayra Moya Espinosa (Ensam Paris), Chenchen Tong (National University of Singapore) and Marek Bucki (Texisense Company) for many interactions and inputs to this study.

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Authors and Affiliations

  1. Univ. Grenoble Alpes, TIMC-IMAG, 38000, Grenoble, France

    Ahmad Bijar & Yohan Payan

  2. CNRS, TIMC-IMAG, 38000, Grenoble, France

    Ahmad Bijar & Yohan Payan

  3. LBM/Institut de Biomécanique Humaine Georges Charpak, 151 Boulevard de l’Hôpital, 75013, Paris, France

    Pierre-Yves Rohan

  4. Univ. Grenoble Alpes, Gipsa-lab, 38000, Grenoble, France

    Ahmad Bijar & Pascal Perrier

  5. CNRS, Gipsa-lab, 38000, Grenoble, France

    Ahmad Bijar & Pascal Perrier

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  1. Ahmad Bijar
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  2. Pierre-Yves Rohan
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  3. Pascal Perrier
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  4. Yohan Payan
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Correspondence to Ahmad Bijar.

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Associate Editor Karol Miller oversaw the review of this article.

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Bijar, A., Rohan, PY., Perrier, P. et al. Atlas-Based Automatic Generation of Subject-Specific Finite Element Tongue Meshes. Ann Biomed Eng 44, 16–34 (2016). https://doi.org/10.1007/s10439-015-1497-y

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