Yifeng Jiang, Erin Edmiston, Fei Wang, Hilary P Blumberg, Lawrence H Staib, Xenophon Papademetris
{"title":"Shape Comparison Using Perturbing Shape Registration.","authors":"Yifeng Jiang, Erin Edmiston, Fei Wang, Hilary P Blumberg, Lawrence H Staib, Xenophon Papademetris","doi":"10.1109/CVPRW.2009.5206598","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":74560,"journal":{"name":"Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"2009 ","pages":"683-690"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CVPRW.2009.5206598","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPRW.2009.5206598","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.