Abstract
Traditional bone atlas modelling is carried out using linear methods such as PCA. Such linear models use a mean shape and principal modes to represent the atlas. A new shape, which is a high dimensional data vector, is then described using this mean and a weighted combination of the principal modes. The use of alternate methods for modelling statistical atlases have not been explored very much. Recently, there has been a lot of new work in the areas of multilinear modelling and nonlinear modelling. They present new ways of modelling high dimensional data. In this work, we compare and contrast several linear, multilinear and nonlinear methods for bone atlas modelling.
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