Shape Comparison Using Perturbing Shape Registration

Shape registration is often involved in computing statistical differences between groups of shapes, which is a key aspect of morphometric study. The results of shape difference are found to be sensitive to registration, i.e., different registration methods lead to varied results. This raises the que...

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Published inProceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 2009; pp. 683 - 690
Main Authors Jiang, Yifeng, Edmiston, Erin, Wang, Fei, Blumberg, Hilary P, Staib, Lawrence H, Papademetris, Xenophon
Format Journal Article
LanguageEnglish
Published 20.06.2009
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ISSN1063-6919
1063-6919
DOI10.1109/CVPRW.2009.5206598

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Summary:Shape registration is often involved in computing statistical differences between groups of shapes, which is a key aspect of morphometric study. The results of shape difference are found to be sensitive to registration, i.e., different registration methods lead to varied results. This raises the question of how to improve the reliability of registration procedures. This paper proposes a perturbation scheme, which perturbs registrations by feeding them with different resampled shape groups, and then aggregates the resulting shape differences. Experiments are conducted using three typical registration algorithms on both synthetic and biomedical shapes, where more reliable inter-group shape differences are found under the proposed scheme.Shape registration is often involved in computing statistical differences between groups of shapes, which is a key aspect of morphometric study. The results of shape difference are found to be sensitive to registration, i.e., different registration methods lead to varied results. This raises the question of how to improve the reliability of registration procedures. This paper proposes a perturbation scheme, which perturbs registrations by feeding them with different resampled shape groups, and then aggregates the resulting shape differences. Experiments are conducted using three typical registration algorithms on both synthetic and biomedical shapes, where more reliable inter-group shape differences are found under the proposed scheme.
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ISSN:1063-6919
1063-6919
DOI:10.1109/CVPRW.2009.5206598