Shock Graphs and Shape Matching
International Journal of Computer Vision
Ligature instabilities in the perceptual organization of shape
Computer Vision and Image Understanding
Multi-scale 3-D Deformable Model Segmentation Based on Medial Description
IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
Statistical Shape Analysis Using Fixed Topology Skeletons: Corpus Callosum Study
IPMI '99 Proceedings of the 16th International Conference on Information Processing in Medical Imaging
Hybrid Boundary-Medial Shape Description for Biologically Variable Shapes
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Segmentation, Registration and measurement of Shape Variation via Image Object Shape
Segmentation, Registration and measurement of Shape Variation via Image Object Shape
Shape versus Size: Improved Understanding of the Morphology of Brain Structures
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Hippocampal Shape Analysis Using Medial Surfaces
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Segmentation of Single-Figure Objects by Deformable M-reps
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Subspace methods for retrieval of general 3D models
Computer Vision and Image Understanding
Statistics of shape via principal geodesic analysis on lie groups
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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Knowledge about the biological variability of anatomical objects is essential for statistical shape analysis and discrimination between healthy and pathological structures. This paper describes a novel approach that incorporates variability of an object population into the generation of a characteristic 3D shape model. The proposed shape representation is based on a fine-scale spherical harmonics (SPHARM) boundary description and a coarse-scale sampled medial description. The medial description is composed of a net of medial samples (m-rep) with fixed graph properties. The medial model is computed automatically from a predefined shape space using pruned 3D Voronoi skeletons to determine the stable medial branching topology. An intrinsic coordinate system and an implicit correspondence between shapes is defined on the medial manifold. Our novel representation describes shape and shape changes in a natural and intuitive fashion. Several experimental studies of biological structures regarding shape asymmetry and similarity clearly demonstrate the meaningful represesentation of local and global form.