Active Shape Models (ASM) offer the possibility to include prior shape knowledge into a statistical shape model. However, the widespread introduction of ASM in 3D medical image analysis is hampered by the need for determining a large collection of corresponding landmarks in a series of images, which is a tedious procedure. In this paper, two different methods for 3D automatic landmarking which were recently introduced by the authors are compared for obtaining an ASM from a large training set of segmented cardiac MR images. The first method uses a volumetric free form deformation to map the landmarks from an atlas to each individual shape. The second method obtains corresponding landmarks by adapting a triangular mesh to the binary images. Compactness and generalizibility results are given for the models that are constructed with both methods, showing that a considerable dimension reduction and small reconstruction error are obtained in both cases
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