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Volumic patient-specific reconstruction of muscular system based on a reduced dataset of medical images

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  • E. Jolivet

Abstract

Three-dimensional mechanical modelling of muscles is essential for various biomechanical applications and clinical evaluation, but it requires a tedious manual processing of numerous images. A muscle reconstruction method is presented based on a reduced set of images to generate an approximate parametric object from basic dimensions of muscle contours. A regular volumic mesh is constructed based on this parametric object. The approximate object and the corresponding mesh are deformed to fit the exact muscles contours yielding patient-specific geometry. Evaluation was performed by comparison of geometry to that obtained by contouring all computed tomography (CT) slices, and by quantification of the mesh quality criteria. Muscle fatty infiltration was estimated using a threshold between fat and muscle. Volumic fat index (VFI) of a muscle was computed using first all the complete CT scan slices containing the muscle (VFIref) and a second time only the slices used for reconstruction (VFIrecons). Mean volume error estimation was 2.6% and hexahedron meshes fulfilled quality criteria. VFIrecons respect the individual variation of fat content.

Suggested Citation

  • E. Jolivet, 2008. "Volumic patient-specific reconstruction of muscular system based on a reduced dataset of medical images," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 11(3), pages 281-290.
    • Handle: RePEc:taf:gcmbxx:v:11:y:2008:i:3:p:281-290
    DOI: 10.1080/10255840801959479
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    Cited by:

    1. A. Assi, 2008. "Subject specific 3D lower limbs muscle reconstructions for children with cerebral palsy," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 11(S1), pages 21-22.
    2. A. Assi, 2008. "Biomechanical analysis of lower limbs for children with cerebral palsy: Gait analysis and musculo-skeletal modelling," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 11(S1), pages 19-20.
    3. G. Dubois & P. Rouch & D. Bonneau & J. L. Gennisson & W. Skalli, 2016. "Muscle parameters estimation based on biplanar radiography," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 19(15), pages 1592-1598, November.
    4. Alexander Wong & Reno Genest & Naveen Chandrashekar & Vivian Choh & Elizabeth Irving, 2012. "Automatic system for 3D reconstruction of the chick eye based on digital photographs," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 15(2), pages 141-149.

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