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pubmed-article:20144190pubmed:abstractTextUsing 3D generic models to statistically analyze trends in biological structure changes is an important tool in morphometrics research. Therefore, 3D generic models built for a range of populations are in high demand. However, due to the complexity of biological structures and the limited views of them that medical images can offer, it is still an exceptionally difficult task to quickly and accurately create 3D generic models (a model is a 3D graphical representation of a biological structure) based on medical image stacks (a stack is an ordered collection of 2D images). We show that the creation of a generic model that captures spatial information exploitable in statistical analyses is facilitated by coupling our generalized segmentation method to existing automatic image registration algorithms.lld:pubmed
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pubmed-article:20144190pubmed:authorpubmed-author:SensenChristo...lld:pubmed
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pubmed-article:20144190pubmed:authorpubmed-author:Meruvia-Pasto...lld:pubmed
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pubmed-article:20144190pubmed:dateRevised2010-9-28lld:pubmed
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pubmed-article:20144190pubmed:articleTitleBuilding generic anatomical models using virtual model cutting and iterative registration.lld:pubmed
pubmed-article:20144190pubmed:affiliationSun Center of Excellence for Visual Genomics, Department of Biochemistry and Molecular Biology, Faculty of Medicine, University of Calgary, 3330 Hospital Drive NW, Calgary, T2N 4N1, Canada. mxiao@ucalgary.ca.lld:pubmed
pubmed-article:20144190pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:20144190pubmed:publicationTypeResearch Support, Non-U.S. Gov'tlld:pubmed