Evaluation of Spherical Parameterization Methods for Three-Dimensional Reconstruction of Medical Images

Abstract:

The spherical parameterization is important for the correspondence problem that is a major part of statistical shape modelling for the reconstruction of patient-specific 3D models from medical images. In this paper, we present comparative studies of five common spherical mapping methods applied to the femur and tibia models: the Issenburg et al. method, the Alexa method, the Saba et al. method, the Praun et al. method and the Shen et al. method. These methods are evaluated using three sets of measures: distortion property, geometric error and distance to standard landmarks. Results show that the Praun et al. method performs better than other methods while the Shen et al. method can be regarded as the most reliable one for providing an acceptable correspondence result. We suggest that the area preserving property can be used as a sufficient condition while the angle preserving property is not important when choosing a spherical mapping method for correspondence application.

• Periodical: Applied Mechanics and Materials (Volumes 365-366)
• Pages: 1342-1349
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.365-366.1342
• Online since: August 2013
• Authors: Xing Hui Wu, Zhi Xiu Hao
• Keywords: Correspondence Problem, Image Visualization, Spherical Parameterization, Statistical Shape Modelling, Three Dimensional Reconstruction

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