Efficient and Accurate Femur Reconstruction using Model-based Segmentation and Superquadric Shapes

R. Cuypers, Z. Tang, W. Luther, and J. Pauli (Germany)


Biomedical engineering, image segmentation, superquad rics, femur modeling, functional parameters


In this paper, we present a new method for the segmenta tion of human bones in MRI (Magnet Resonance Imag ing) scan images. To illustrate the approach, we focus on the modeling of a real femur. Region growing and thresh old methods are used for pre-processing. For some areas of bones, for example, the femur ball, we use a VRML (Virtual Reality Modeling Language)-based femur model as a reference in order to make the segmentation method more robust in its response to noise and the influence of other tissues with the same grey level as bones. In paral lel, we propose an accurate and efficient geometric fitting and reconstruction model using a composite superquadric (SQ) model. The accuracy of the algorithm is demon strated through the reconstruction of a femur dataset and further functional parameters in comparison with manual extraction and the VRML-based approach.

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