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    Joint Surface Modeling with Thin-Plate Splines

    19063_downloaded_stream_155.pdf (530.0Kb)
    Access Status
    Open access
    Authors
    Boyd, S.
    Ronsky, J.
    Lichti, Derek
    Salkauskas, D.
    Chapman, M.
    Date
    1999
    Type
    Journal Article
    
    Metadata
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    Citation
    Boyd, S.K. and Ronsky, J.L. and Lichti, D.D. and Salkauskas, D. and Chapman, M.A.. 1999. Joint Surface Modeling with Thin-Plate Splines. Journal of Biochemical Engineering 121 (5): 525-532.
    Source Title
    Journal of Biochemical Engineering
    Faculty
    Division of Resources and Environment
    Department of Spatial Sciences
    URI
    http://hdl.handle.net/20.500.11937/34115
    Collection
    • Curtin Research Publications
    Abstract

    Mathematical joint surface models based on experimentally determined data points can be used to investigate joint characteristics such as curvature, congruency, cartilage thickness, joint contact areas, as well as to provide geometric information well suited for finite element analysis. Commonly, surface modeling methods are based on B-splines, which involve tensor products. These methods have had success; however, they are limited due to the complex organizational aspect of working with surface patches, and modeling unordered, scattered experimental data points. An alternative method for mathematical joint surface modeling is presented based on the thin-plate spline (TPS). It has the advantage that it does not involve surface patches, and can model scattered data points without experimental data preparation. An analytical surface was developed and modeled with the TPS to quantify its innterpolating and smoothing characteristics. Some imitations of the TPS include discontinuity of curvature at exactly the experimental surface data points, and numerical problems dealing with data sets in excess of 2000 points. However, suggestions for overcoming these limitations are presented. Testing the TPS with real experimental data, the patellofemoral joint of a cat was measured with multistation digital photogrammetry and modeled using the TPS to determine cartilage hicknesses and surface curvature. The cartilage thickness distribution ranged between 100 to 550 pm on the patella, and 100 to 300 pm on the femur. It was found that the TPS was an effective tool for modeling joint surfaces because no preparation of the experimental data points was necessary, and the resulting unique function representing the entire surface does not involve surface parches. A detailed algorithm is presented for implementation of the TPS.

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