  Partial Volume effects are present at the boundary between any two types of
material in a CT image due to the scanner's Point Spread Function, finite voxel
resolution, and importantly, the discrepancy in radiodensity between the two
materials. In this study a new algorithm is developed and validated that builds
on previously published work to enable the correction of partial volume effects
at cortical bone boundaries. Unlike past methods, this algorithm does not
require pre-processing or user input to achieve the correction, and the
correction is applied directly onto a set of CT images, which enables it to be
used in existing computational modelling workflows. The algorithm was validated
by performing experimental three point bending tests on porcine fibulae
specimen and comparing the experimental results to finite element results for
models created using either the original, uncorrected CT images or the partial
volume corrected images. Results demonstrated that the models created using the
partial volume corrected images did improved the accuracy of the surface strain
predictions. Given this initial validation, this algorithm is a viable method
for overcoming the challenge of partial volume effects in CT images. Thus,
future work should be undertaken to further validate the algorithm with human
tissues and through coupling it with a range of different finite element
creation workflows to verify that it is robust and agnostic to the chosen
material mapping strategy.
