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Title: Automated method for computing the morphological and clinical parameters of the proximal femur using heuristic modeling techniques
Authors: Cerveri, Pietro ×
Marchente, Mario
Bartels, Ward
Corten, Kristoff
Simon, Jean-Pierre
Manzotti, Alfonso #
Issue Date: May-2010
Publisher: Blackwell Scientific Publications
Series Title: Annals of Biomedical Engineering vol:38 issue:5 pages:1752-1766
Abstract: Bone morphology and morphometric measurements of the lower limb provide significant and useful information for computer-assisted orthopedic surgery planning and intervention, surgical follow-up evaluation, and personalized prosthesis design. Femoral head radius and center, neck axis and size, femoral offset and shaft axis are morphological and functional parameters of the proximal femur utilized both in diagnosis and therapy. Obtaining this information from image data without any operator supervision or manual editing remains a practical objective to avoid variability intrinsic in the manual analysis. In this article, we propose a heuristic method that automatically computes the proximal femur morphological parameters by processing the mesh surface of the femur. The surface data are sequentially processed using geometrical properties such as symmetries, asymmetries, and principal elongation directions. Numerical methods identify the axis of the shaft of femur (least squares cylinder fitting), the head surface and center (least squares sphere fitting), and the femur neck axis and radius (minimal area of the cross section by evolutionary optimization). The repeatability of the method was tested upon 20 femur (10 left + 10 right) surfaces reconstructed from CT scans taken on cadavers. The repeatability error of the automated computation of anatomical landmarks, angles, sizes, and axes was less than 1.5 mm, 2.5 degrees, 1.0 mm, and 3.5 mm, respectively. The computed parameters were in good agreement (landmark difference: <2.0 mm; angle difference: <2.0 degrees; axes difference: <2.5 degrees; size difference: <1.5 mm) with the corresponding reference parameters manually identified in the original CT images by medical experts. In conclusion, the proposed method can improve the degree of automation of model-based hip replacement surgical systems.
URI: 
ISSN: 0090-6964
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Orthopaedics Section (-)
Biomechanics Section
× corresponding author
# (joint) last author

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