Accuracy assessment of CT-based outer surface femur meshes.
OBJECTIVE
Computer-aided bone surgery planning and implant design applications require accurate and compact representations of the patient's bone. The accuracy of bone segmentation from medical images has been studied extensively, with each study using a specific ground truth and a specific type and number of accuracy measurements. However, for convenience and practical reasons these three specifications have always been limited. The goal of this study is to thoroughly assess the absolute 3D accuracy of CT-based bone outer surface meshes, using femora as the examples.


METHODS
Using dense and very accurate optical surface scans of 15 dried femora as an absolute ground truth, this paper reports on the absolute 3D geometric accuracy of triangulated bone outer surface meshes, which were segmented from the CT scans of the corresponding formalin-fixed intact cadaver specimens using the author's previously presented contour-based segmentation algorithm on the one hand, and the commercially available Mimics(R) software (Materialise N.V., Leuven, Belgium) on the other. The study incorporates the effect of soft tissue presence on hard tissue segmentation and simultaneously reveals the accuracy shift introduced as a result of boiling the cadaver bones by processing extra CT scans of the dried bones.


RESULTS
The presented study demonstrates that, when using the optimal parameter settings for the respective segmentation procedures, sub-voxel mesh accuracies can be attained. Compact surface representations of femora can be generated with mean absolute accuracies of up to one fifth of the voxel size and Root Mean Square (RMS) error of half the voxel size.


CONCLUSIONS
The 3D accuracy of the contour-based segmentation previously presented by the author makes it most suitable for generating outer bone surface meshes for use in the aforementioned applications. The optimal parameter settings for this segmentation procedure have been identified. For the Mimics bone surface meshes, a single, but excellent, pre-defined set of parameters was identified.
Gelaude
F
F
Division of Biomechanics and Engineering Design, Katholieke Universiteit Leuven, Leuven, Belgium. frederik.gelaude@mech.kuleuven.be
Vander Sloten
J
J
Lauwers
B
B
D000369:Aged, 80 and over; D000465:Algorithms; D002102:Cadaver; D005260:Female; D005269:Femur / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D012984:Software; D036542:Tomography, Spiral Computed