Real-Time Estimation of Hip Range of Motion for Total Hip Replacement Surgery

  • Yasuhiro Kawasaki
  • Fumihiko Ino
  • Yoshinobu Sato
  • Nobuhiko Sugano
  • Hideki Yoshikawa
  • Shinichi Tamura
  • Kenichi Hagihara
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3217)

Abstract

This paper presents the design and implementation of a range of motion estimation method that is capable of fine-grained estimation during total hip replacement (THR) surgery. Our method combines an adaptive refinement strategy with a high performance computing system in order to enable real-time estimation. The experimental results indicate that the implementation on a cluster of 64 PCs enables intraoperative estimation of 360 × 360 × 180 stance configurations within a half minute, and thereby plays a key role in selecting and aligning the optimal combination of artificial joint components during THR surgery.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    DiGioia, A.M., et al.: Image guided navigation system to measure intraoperatively acetabular implant alignment. Clinical Orthopaedics and Related Research 355, 8–22 (1998)CrossRefGoogle Scholar
  2. 2.
    Jaramaz, B., et al.: Computer assisted measurement of cup placement in total hip replacement. Clinical Orthopaedics and Related Research 354, 70–81 (1998)CrossRefGoogle Scholar
  3. 3.
    Sato, Y., et al.: Intraoperative simulation and planning using a combined acetabular and femoral (CAF) navigation system for total hip replacement. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 1114–1125. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  4. 4.
    Richolt, J.A., et al.: Impingement simulation of the hip in SCFE using 3D models. Computer Aided Surgery 4, 144–151 (1999)CrossRefGoogle Scholar
  5. 5.
    Kang, M., et al.: Accurate simlation of hip joint range of motion. In: Proc. 15th Int’l Conf. Computer Animation (CA 2002), pp. 215–219 (2002)Google Scholar
  6. 6.
    Kawasaki, Y., et al.: High-performance computing service over the Internet for intraoperative image processing. IEEE Trans. Information Technology in Biomedicine 8, 36–46 (2004)CrossRefGoogle Scholar
  7. 7.
    Boden, N.J., et al.: Myrinet: A gigabit-per-second local-area network. IEEE Micro 15, 29–36 (1995)CrossRefGoogle Scholar
  8. 8.
    O’Carroll, F., et al.: The design and implementation of zero copy MPI using commodity hardware with a high performance network. In: Proc. 12th ACM Int’l Conf. Supercomputing (ICS 1998), pp. 243–250 (1998)Google Scholar
  9. 9.
    : Message Passing Interface Forum: MPI: A message-passing interface standard. Int’l J. Supercomputer Applications and High Performance Computing 8, 159–416 (1994)Google Scholar
  10. 10.
    Gottschalk, S., et al.: OBBTree: A hierarchical structure for rapid interference detection. In: Computer Graphics (Proc. ACM SIGGRAPH 1996), vol. 30, pp. 171–180 (1996)Google Scholar
  11. 11.
    Hudson, T.C., et al.: V-COLLIDE: Accelerated collision detection for VRML. In: Proc. 2nd Symp. Virtual Reality Modeling Language, VRML 1997, pp. 117–124 (1997)Google Scholar
  12. 12.
    Sugano, N., et al.: Accuracy evaluation of surface-based registration methods in a computer navigation system for hip surgery performed through a posterolateral approach. Comput. Aided Surgery 6, 195–203 (2001)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Yasuhiro Kawasaki
    • 1
  • Fumihiko Ino
    • 1
  • Yoshinobu Sato
    • 2
  • Nobuhiko Sugano
    • 2
  • Hideki Yoshikawa
    • 2
  • Shinichi Tamura
    • 2
  • Kenichi Hagihara
    • 1
  1. 1.Graduate School of Information Science and TechnologyOsaka University 
  2. 2.Graduate School of MedicineOsaka University 

Personalised recommendations