Abstract
Although morphological analyses of craniofacial bones are very important in the anatomy field, previous research has not covered there multivariate analyses, which are important to understand there global statistic properties. In this study, we first applied the principal component analysis (PCA) to 48 sample bone shapes extracted from CT data. The analysis revealed that the bone shapes can be well represented by just 35 principal components. Further, we applied the independent component analysis and compared the results with those from PCA.
