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Objectives: 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. Materials and 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 Õ 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 Õ bone surface meshes, a single, but excellent, pre-defined set of parameters was identified.

Custom implants are used to treat patients with large acetabular bone defects. To quantify the bone defect and to initialize the implant design, a virtual anatomical reconstruction of the bone needs to be performed. Our SSM-based reconstruction approach was used to overcome the limitations of the mirrored contralateral method and improves upon other SSM reconstruction techniques. The reconstruction errors for the acetabular direction, the hip joint center and the acetabular radius were, respectively: [Formula: see text], 2.6 mm and 0.7 mm. We believe that our method can be an essential tool in the planning and the design of custom implants.

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Good segmentation of the outer bone cortex from medical images is a prerequisite for applications in the field of finite element analysis, surgical planning environments and personalised, case dependent, bone reconstruction. However, current segmentation procedures are often unsatisfactory. This study presents an automated filter procedure to generate a set of adapted contours from which a surface mesh can be deduced directly. The degree of interaction is user determined. The bone contours are extracted from the patients CT data by quick grey value segmentation. An extended filter procedure then only retains contour information representing the outer cortex as more specific internal loops and shape irregularities are removed, tailoring the image for the above-mentioned applications. The developed medical image based design methodology to convert contour sets of multiple bone types, from tibia tumour to neurocranium, is reported and discussed.