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Reconstruction of 3D Muscle Fiber Structure Using High Resolution Cryosectioned Volume

  • Yoshito OtakeEmail author
  • Kohei Miyamoto
  • Axel Ollivier
  • Futoshi Yokota
  • Norio Fukuda
  • Lauren J. O’Donnell
  • Carl-Fredrik Westin
  • Masaki Takao
  • Nobuhiko Sugano
  • Beom Sun Chung
  • Jin Seo Park
  • Yoshinobu Sato
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10734)

Abstract

Three-dimensional (3D) muscle fiber architecture is important in patient-specific biomechanical simulation. While several in-vivo methods using diffusion tensor imaging and ultrasound have been demonstrated their feasibility in reconstruction of the fiber architecture, the main challenge is the lack of gold standard. Although physical measurement from cadavers has been considered as the accurate way of determining 3D muscle fiber architecture, its downsides include error in the manual tracing and the labor intensive process allowing only sparse sampling of a particular muscle. We propose an alternative method of obtaining a dense fiber architecture of multiple muscles in close proximity using high resolution cryosectioned images. Similar to the diffusion tensor imaging, we first extract the local orientation at each voxel using the structure tensor analysis and then tractography algorithm is applied to obtain stream lines. The proposed method was applied to all muscles around the hip joint and the masticatory muscles. Qualitative comparison with the anatomy textbook indicated that the proposed method reconstructed a plausible muscle fiber architecture. We plan to make the reconstructed fiber architecture of whole body muscles publicly available in order to serve for the biomechanics community.

Keywords

Muscle fiber architecture Gold standard High resolution cryosectioned images 

Notes

Acknowledgements

This research was supported by MEXT/JSPS KAKENHI 26108004, JST PRESTO 20407, and AMED/ETH the strategic Japanese-Swiss cooperative research program, NIH grant U01CA199459 and P41EB015902.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Yoshito Otake
    • 1
    Email author
  • Kohei Miyamoto
    • 1
  • Axel Ollivier
    • 1
    • 2
  • Futoshi Yokota
    • 1
  • Norio Fukuda
    • 1
  • Lauren J. O’Donnell
    • 3
  • Carl-Fredrik Westin
    • 3
  • Masaki Takao
    • 4
  • Nobuhiko Sugano
    • 4
  • Beom Sun Chung
    • 5
  • Jin Seo Park
    • 6
  • Yoshinobu Sato
    • 1
  1. 1.Graduate School of Information ScienceNara Institute of Science and TechnologyIkomaJapan
  2. 2.Ecole Nationale Supérieure d’Ingénieurs de CaenCaenFrance
  3. 3.Harvard Medical SchoolBrigham and Women’s HospitalBostonUSA
  4. 4.Graduate School of MedicineOsaka UniversitySuitaJapan
  5. 5.Department of Anatomy, School of MedicineAjou UniversitySuwonSouth Korea
  6. 6.School of MedicineDongguk UniversitySeoulSouth Korea

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