Rigid, affine and locally affine registration of free-form surfaces
International Journal of Computer Vision
Automatic Landmark Identification Using a New Method of Non-rigid Correspondence
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
Contour Regularity Extraction Based on String Edit Distance
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
Characterization of contour regularities based on the Levenshtein edit distance
Pattern Recognition Letters
Unsupervised clustering of shapes
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
An improved fast edit approach for two-string approximated mean computation applied to OCR
Pattern Recognition Letters
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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.