Automatic meshing of femur cortical surfaces from clinical CT images

Authors:
Ju Zhang;Duane Malcolm;Jacqui Hislop-Jambrich;C. David L. Thomas;Poul Nielsen
Affiliations:
Auckland Bioengineering Institute, The University of Auckland, New Zealand;Auckland Bioengineering Institute, The University of Auckland, New Zealand;Clinical Applications Research Center, Toshiba Medical, Sydney, Australia;The Melbourne Dental School, The University of Melbourne, Victoria, Australia;Auckland Bioengineering Institute, The University of Auckland, New Zealand,Department of Engineering Science, The University of Auckland, New Zealand
Venue:
MeshMed'12 Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis
Year:
2012

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Abstract

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.