ACM Computing Surveys (CSUR)
Biomechanics and the Cyberhuman
IEEE Computer Graphics and Applications
Feature-based similarity search in 3D object databases
ACM Computing Surveys (CSUR)
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
Patient specific dosimetry phantoms using multichannel LDDMM of the whole body
Journal of Biomedical Imaging - Special issue on Parallel Computation in Medical Imaging Applications
Moments of superellipsoids and their application to range image registration
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Segmentation of abdominal organs from CT using a multi-level, hierarchical neural network strategy
Computer Methods and Programs in Biomedicine
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The morphological similarity of organs is studied with feature vectors based on geometric and Zernike 3D moments. It is particularly investigated if outliers and average models can be identified. For this purpose, the relative proximity to the mean feature vector is defined, principal coordinate and clustering analyses are also performed. To study the consistency and usefulness of this approach, 17 livers and 76 hearts voxel models from several sources are considered. In the liver case, models with similar morphological feature are identified. For the limited amount of studied cases, the liver of the ICRP male voxel model is identified as a better surrogate than the female one. For hearts, the clustering analysis shows that three heart shapes represent about 80% of the morphological variations. The relative proximity and clustering analysis rather consistently identify outliers and average models. For the two cases, identification of outliers and surrogate of average models is rather robust. However, deeper classification of morphological feature is subject to caution and can only be performed after cross analysis of at least two kinds of feature vectors. Finally, the Zernike moments contain all the information needed to re-construct the studied objects and thus appear as a promising tool to derive statistical organ shapes.