Learning Shape Models from Examples Using Automatic Shape Clustering and Procrustes Analysis

A new fully automated shape learning method is presented. It is based on clustering a shape training set in the original shape space and performing a Procrustes analysis on each cluster to obtain a cluster prototype and information about shape variation. As a direct application of our shape learning method, a 17-structure shape model of brain substructures was computed from MR image data, an eigen-shape model was automatically derived. Our approach can serve as an automated substitute to the tedious and time-consuming manual shape analysis.

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