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JACIII Vol.14 No.2 pp. 122-127
doi: 10.20965/jaciii.2010.p0122
(2010)

Paper:

Fuzzy Visual Hull Algorithm for Three-Dimensional Shape Reconstruction of TKA Implants from X-Ray Cone-Beam Images

Syoji Kobashi*1,*2, Nao Shibanuma*3,*4, and Yutaka Hata*1,*2

*1Graduate School of Engineering, University of Hyogo, 2167 Shosha, Himeji, Hyogo 671-2280, Japan

*2WPI Immunology Frontier Research Center, Osaka University

*3Kobe Kaisei Hospital, Japan

*4Graduate School of Medicine, Kobe University, Japan

Received:
April 24, 2009
Accepted:
October 6, 2009
Published:
March 20, 2010
Keywords:
3-D reconstruction, fuzzy logic, visual hull algorithm, total knee arthroplasty
Abstract

Three-Dimensional (3-D) shape reconstruction of total knee arthroplasty (TKA) implants in vivo plays a key role to investigate implanted knee kinematics. TKA implants typically consist of metal femoral and tibial components and a polyethylene tibial insert. X-ray computed tomography (CT) causes severe metal artifacts, making the 3-D shape in reconstructed images extremely difficult to understand. This article proposes a new method of 3-D reconstruction from X-ray cone-beam images. Called a fuzzy visual hull, it introduces fuzzy logic in recognizing X-ray images. X-ray cone-beam images are fuzzified and back-projected into a fuzzy voxel space. Defuzzifying the fuzzy voxel space enables the 3-D TKA implant shape to be reconstructed. The results of evaluation using TKA implants in vitro and computer-synthesized images demonstrated that the fuzzy visual hull provides high robustness against noise added to X-ray cone-beam images. The new approach also reconstructed the 3-D polyethylene insert despite the difficulty of recognizing the region in conventional X-ray CT.

Cite this article as:
S. Kobashi, N. Shibanuma, and Y. Hata, “Fuzzy Visual Hull Algorithm for Three-Dimensional Shape Reconstruction of TKA Implants from X-Ray Cone-Beam Images,” J. Adv. Comput. Intell. Intell. Inform., Vol.14, No.2, pp. 122-127, 2010.
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Last updated on Jul. 23, 2019