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Local Shape Analysis Using MANCOVA
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Institution: |
The University of North Carolina at Chapel Hill |
Publisher: |
The Insight Journal |
Publication Date: |
Jul-2009 |
Citation: |
The Insight Journal - 2009 July-December |
Links: |
http://hdl.handle.net/10380/3124
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Keywords: |
Projects:LocalStatisticalAnalysisViaPermutationTests, Projects:ShapeAnalysisFrameworkUsingSPHARMPDM, Statistical shape analysis, MANCOVA, Multiple comparison problem, permutation tests, SPHARM |
Appears in Collections: |
NA-MIC |
Sponsors: |
NIDCR (DE018962) NAMIC (U54 EB005149 NDRC (UNC P30 HD03110) |
Generated Citation: |
Paniagua B., Styner M., Macenko M., Pantazis D., Niethammer M. Local Shape Analysis Using MANCOVA. The Insight Journal - 2009 July-December |
| Downloaded: | 232 times. [view map] |
| Paper: | Download, View online |
| Export citation: |
Gross shape measures such as volume have been widely used in statistical analysis of anatomical structures. Statistical shape analysis methods have emerged within the last decade to allow for a localized analysis of shape. Most shape analysis frameworks are though lacking a good statistical underpinning, as they commonly do not allow for the inclusion of independent variables such as age, gender or clinical scores. This work presents a unified method for local shape analysis that can accomodate different number of variates and contrasts. It also allows to include any number of associated variables in the statistical analysis of the data. Several cases of study are given to clarify the explanation of the different types of data that can be analyzed and the parameters that can be used to tune the program shapeAnalysisMAN- COVA. This tool has been designed to interact seamlessly with the existing UNC SPHARM-PDM [27] based shape analysis toolbox.
Additional Material
1 File (138.83kB)
Paniagua-InsightJournal2009-fig11.jpg (138.83kB)