Comput Methods Programs Biomed - Comparison of organs' shapes with geometric and Zernike 3D moments.

Tópicos

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Resumo

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.

Resumo Limpo

morpholog similar organ studi featur vector base geometr zernik d moment particular investig outlier averag model can identifi purpos relat proxim mean featur vector defin princip coordin cluster analys also perform studi consist use approach liver heart voxel model sever sourc consid liver case model similar morpholog featur identifi limit amount studi case liver icrp male voxel model identifi better surrog femal one heart cluster analysi show three heart shape repres morpholog variat relat proxim cluster analysi rather consist identifi outlier averag model two case identif outlier surrog averag model rather robust howev deeper classif morpholog featur subject caution can perform cross analysi least two kind featur vector final zernik moment contain inform need reconstruct studi object thus appear promis tool deriv statist organ shape

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