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32

IPMI
2005
Springer

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Hypothesis Testing with Nonlinear Shape Models

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Hypothesis Testing with Nonlinear Shape Models

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We present a method for two-sample hypothesis testing for statistical shape analysis using nonlinear shape models. Our approach uses a true multivariate permutation test that is invariant to the scale of different model parameters and that explicitly accounts for the dependencies between variables. We apply our method to m-rep models of the lateral ventricles to examine the amount of shape variability in twins with different degrees of genetic similarity.

Timothy B. Terriberry, Sarang C. Joshi, Guido Geri

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IPMI 2005 | Medical Imaging | Nonlinear Shape Models | Shape Variability | Statistical Shape Analysis |

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Added	16 Nov 2009
Updated	16 Nov 2009
Type	Conference
Year	2005
Where	IPMI
Authors	Timothy B. Terriberry, Sarang C. Joshi, Guido Gerig

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