Hypothesis testing with nonlinear shape models

Timothy B. Terriberry; Sarang C. Joshi; Guido Gerig

Hypothesis testing with nonlinear shape models

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science
Editors	G.E. Christensen, M. Sonka
Pages	15-26
Number of pages	12
Volume	3565
State	Published - 2005
Event	19th International Conference on Information Processing in Medical Imaging, IPMI 2005 - Glenwood Springs, CO, United States Duration: Jul 10 2005 → Jul 15 2005

Other

Other	19th International Conference on Information Processing in Medical Imaging, IPMI 2005
Country/Territory	United States
City	Glenwood Springs, CO
Period	7/10/05 → 7/15/05

ASJC Scopus subject areas

Computer Science (miscellaneous)

Cite this

@inproceedings{32fe4a9cf37d43ceb474eebf482498ab,

title = "Hypothesis testing with nonlinear shape models",

abstract = "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.",

author = "Terriberry, {Timothy B.} and Joshi, {Sarang C.} and Guido Gerig",

year = "2005",

language = "English (US)",

volume = "3565",

pages = "15--26",

editor = "G.E. Christensen and M. Sonka",

booktitle = "Lecture Notes in Computer Science",

note = "19th International Conference on Information Processing in Medical Imaging, IPMI 2005 ; Conference date: 10-07-2005 Through 15-07-2005",

}

TY - GEN

T1 - Hypothesis testing with nonlinear shape models

AU - Terriberry, Timothy B.

AU - Joshi, Sarang C.

AU - Gerig, Guido

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=26444570385&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=26444570385&partnerID=8YFLogxK

M3 - Conference contribution

C2 - 17354681

AN - SCOPUS:26444570385

VL - 3565

SP - 15

EP - 26

BT - Lecture Notes in Computer Science

A2 - Christensen, G.E.

A2 - Sonka, M.

T2 - 19th International Conference on Information Processing in Medical Imaging, IPMI 2005

Y2 - 10 July 2005 through 15 July 2005

ER -

Hypothesis testing with nonlinear shape models

Abstract

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ASJC Scopus subject areas

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