Automatic Meshing of Femur Cortical Surfaces from Clinical CT Images

We present an automated image-to-mesh workflow that meshes the cortical surfaces of the human femur, from clinical CT images. A piecewise parametric mesh of the femoral surface is customized to the in-image femoral surface by an active shape model. Then, by using this mesh as a first approximation, we segment cortical surfaces via a model of cortical morphology and imaging characteristics. The mesh is then customized further to represent the segmented inner and outer cortical surfaces. We validate the accuracy of the resulting meshes against an established semi-automated method. Root mean square error for the inner and outer cortical meshes were 0.74 mm and 0.89 mm, respectively. Mean mesh thickness absolute error was 0.03 mm with a standard deviation of 0.60 mm. The proposed method produces meshes that are correspondent across subjects, making it suitable for automatic collection of cortical geometry for statistical shape analysis.

[1]  I. Jolliffe Principal Component Analysis , 2002 .

[2]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[3]  T J Beck,et al.  Does Body Size Account for Gender Differences in Femur Bone Density and Geometry? , 2001, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[4]  C. Thomas,et al.  A morphometric study of the cortex of the human femur from early childhood to advanced old age. , 1995, Forensic science international.

[5]  Andrew H. Gee,et al.  High resolution cortical bone thickness measurement from clinical CT data , 2010, Medical Image Anal..

[6]  R Zdero,et al.  The effect of cortex thickness on intact femur biomechanics: A comparison of finite element analysis with synthetic femurs , 2010, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[7]  G. Holzer,et al.  Hip Fractures and the Contribution of Cortical Versus Trabecular Bone to Femoral Neck Strength , 2009, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[8]  Timo Jämsä,et al.  Combination of bone mineral density and upper femur geometry improves the prediction of hip fracture , 2004, Osteoporosis International.

[9]  Thomas W. Sederberg,et al.  Free-form deformation of solid geometric models , 1986, SIGGRAPH.

[10]  G. Dougherty,et al.  Measurement of thickness and density of thin structures by computed tomography: a simulation study. , 1999, Medical physics.

[11]  T N Hangartner,et al.  Race and sex differences in bone mineral density and geometry at the femur. , 2009, Bone.

[12]  C. Goodall Procrustes methods in the statistical analysis of shape , 1991 .

[13]  A. J. Pullan,et al.  Geometric modeling of the human torso using cubic hermite elements , 2007, Annals of Biomedical Engineering.

[14]  C. Thomas,et al.  Relation between age, femoral neck cortical stability, and hip fracture risk , 2005, The Lancet.

[15]  Hans-Peter Meinzer,et al.  Statistical shape models for 3D medical image segmentation: A review , 2009, Medical Image Anal..