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JACIII Vol.19 No.3 pp. 372-380
doi: 10.20965/jaciii.2015.p0372
(2015)

Paper:

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Fully Automated Determination of Femoral Coordinate System in CT Image Based on Epicondyles

Yosuke Uozumi*, Kouki Nagamune*,**, Naoki Nakano**, Kanto Nagai**, Daisuke Araki**, Yuichi Hoshino**,***, Takehiko Matsushita**, Ryosuke Kuroda**, and Masahiro Kurosaka**

*Graduate School of Engineering, University of Fukui
3-9-1 Bunkyo, Fukui 910-8507, Japan

**Graduate School of Medicine, Kobe University
7-5-2 Kusunoki-cho, Chuo-ku, Kobe 650-0017, Japan

***Kaisei Hospital
3-11-15 Shinohara Kitamachi, Nada-Ku, Kobe 657-0068, Japan

Received:
August 27, 2014
Accepted:
February 10, 2015
Published:
May 20, 2015
Creative Commons License
Keywords:
CT image, knee, femur, coordinate system
Abstract
We propose a fully automated determination of the femoral coordinates in computerized tomography (CT) imaging based on epicondyles. The challenge point of this paper is that we take up how to calculate the femoral coordinate system (FCS), which is difficult to determine automatically. Our proposed method automatically determines the FCS based on anatomical reference points. We evaluated 10 subjects (six men and four women 28.9 ± 9.3 years old, three left-handed and seven right-handed) who had no history of joint injury. We examined the proposed method by comparing the expert and algorithm. The medial epicondyle was 1.41 ± 0.75 mm p = 0.42 > 0.05, student’s t test) in positioning accuracy. The lateral epicondyle was 1.36 ± 0.70 mm p = 0.42) in positioning accuracy. The origin was 0.87 ± 0.40 mm p = 0.71). in positioning accuracy. The lateral axis angle accuracy was 0.53 ± 0.84° p = 0.44). In short, the proposed method constructed patient-specific coordinate systems more accurately than expert manual.
Cite this article as:
Y. Uozumi, K. Nagamune, N. Nakano, K. Nagai, D. Araki, Y. Hoshino, T. Matsushita, R. Kuroda, and M. Kurosaka, “Fully Automated Determination of Femoral Coordinate System in CT Image Based on Epicondyles,” J. Adv. Comput. Intell. Intell. Inform., Vol.19 No.3, pp. 372-380, 2015.
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References
  1. [1] E. S. Grood and W. J. Suntay, “A joint coordinate system for the clinical description of three-dimensional motions: application to the knee,” J. of biomechanical engineering, Vol.105, No.2, pp. 136-144, 1983.
  2. [2] S. Wei, K. McQuade, and G. Smidt, “Three-dimensional joint range of motion measurements from skeletal coordinate data,” The J. of Orthopaedic and Sports Physical Therapy, Vol.18, No.6, pp. 687, 1993.
  3. [3] N. Baka, B. L. Kaptein, J. E. Giphart, M. Staring, M. d. Bruijne, B. P. Lelieveldt, and E. Valstar, “Evaluation of automated statistical shape model based knee kinematics from biplane fluoroscopy,” J. of Biomechanics, Vol.47, No.1, pp. 122-129, 2014.
  4. [4] N. Baka, M. d. Bruijne, T. v. Walsum, B. Kaptein, J. Giphart, M. Schaap, W. J. Niessen, and B. P. Lelieveldt, “Statistical Shape Model-Based Femur Kinematics From Biplane Fluoroscopy,” IEEE Trans. on Medical Imaging, Vol.31, No.8, pp. 1573-1583, 2012.
  5. [5] N. Hagemeister, G. Parent, M. V. d. Putte, N. St-Onge, N. Duval, and J. d. Guise, “A reproducible method for studying three dimensional knee kinematics,” J. of Biomechanics, Vol.38, No.9, pp. 1926-1931, 2005.
  6. [6] C.-C. Lin, S. Zhang, J. Frahm, T.-W. Lu, C.-Y. Hsu, and T.-F. Shih, “A slice-to-volume registration method based on real-time magnetic resonance imaging for measuring three-dimensional kinematics of the knee,” Medical physics, Vol.40, No.10, pp. 102302, 2013.
  7. [7] M. P. Kadaba, H. Ramakrishnan, and M. Wootten, “Measurement of lower extremity kinematics during level walking,” J. of Orthopaedic Research, Vol.8, No.3, pp. 383-392, 1990.
  8. [8] D. L. Miranda, M. J. Rainbow, E. L. Leventhal, J. J. Crisco, and B. C. Fleming, “Automatic determination of anatomical coordinate systems for three-dimensional bone models of the isolated human knee,” J. of biomechanics, Vol.43, No.8, pp. 1623-1626, 2010.
  9. [9] S. Kai, T. Sato, Y. Koga, G. Omori, K. Kobayashi, M. Sakamoto, and Y. Tanabe, “Automatic construction of an anatomical coordinate system for three-dimensional bone models of the lower extremities. Pelvis, femur, and tibia,” J. of biomechanics, Vol.47, No.5, pp. 1229-1233, 2014.
  10. [10] R. Siebold, J. Axe, J. J. Irrgang, K. Li, S. Tashman, and F. H. Fu, “A computerized analysis of femoral condyle radii in ACL intact and contralateral ACL reconstructed knees using 3D CT,” Knee surgery, sports traumatology, arthroscopy, Vol.18, No.1, pp. 26-31, 2010.
  11. [11] Y. Uozumi, K. Nagamune, D. Araki, Y. Hoshino, T. Matsushita, R. Kuroda, and M. Kurosaka, “A Bone Segmentation for the Knee Joint in MDCT Image Based on Anatomical Information,” Int. J. of Intelligent Computing in Medical Sciences & Image Processing (IC-MED), Vol.5, No.2, pp. 105-113, 2013.
  12. [12] Y. Uozumi, K. Nagamune, Y. Nishizawa, D. Araki, Y. Hoshino, T. Matsushita, R. Kuroda, and M. Kurosaka, “An Automatic Three- Dimensional Evaluation of Screw Placement After Anterior Cruciate Ligament Reconstruction Using MDCT Images,” J. of Advanced Computational Intelligence and Intelligent Informatics (JACIII), Vol.17, No.6, pp. 818-827, 2013.
  13. [13] Y. Uozumi, K. Nagamune, D. Araki, Y. Hoshino, R. Kuroda, and M. Kurosaka, “An Automated Analysis for Anatomical Structure of Distal Femur from MDCT Image by Contour Tracing,” Proc. of the 9th Int. Conf. on Signal Image Technology & Internet Based Systems (SITIS), pp. 842-847, Kyoto, Japan, 2013.
  14. [14] F. A. Mettler Jr, W. Huda, T. T. Yoshizumi, and M. Mahesh, “Effective Doses in Radiology and Diagnostic Nuclear Medicine: A Catalog 1,” Radiology, Vol.248, No.1, pp. 254-263, 2008.

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