An Integrated Approach for Reconstructing a Surface Model of the Proximal Femur from Sparse Input Data and a Multi-Level Point Distribution Model

摘要

In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific surface model of the proximal femur from intra-operatively available sparse data, which may consist of sparse point data or a limited number of calibrated fluoroscopic images. We conducted experiments on clinical datasets as well as on datasets from cadaveric bones. Our experimental results demonstrate promising accuracy of the present approach. Further extension to reconstructing a surface model from pre-operative biplanar X-ray radiographs is discussed.