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Proceedings Paper

Robust registration for change detection
Author(s): Sune Darkner; Dan Witzner Hansen; Rasmus R. Paulsen; Rasmus Larsen
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Paper Abstract

We address the problem of intra-subject registration for change detection. The goal is to separate stationary and changing subsets to be able to robustly perform rigid registration on the stationary subsets and thus improve the subsequent change detection. An iterative approach using a hybrid of parametric and non-parametric statistics is presented. The method uses non-parametric clustering and large scale hypothesis testing with estimation of the empirical null hypothesis. The method is successfully applied to 3D surface scans of human ear impressions containing true changes as well as data with synthesized changes. It is shown that the method improves registration and is capable of reducing the difference between registration using different norms.

Paper Details

Date Published: 26 March 2008
PDF: 8 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69142T (26 March 2008); doi: 10.1117/12.770106
Show Author Affiliations
Sune Darkner, Technical Univ. of Denmark (Denmark)
Eriksholm Research Ctr. (Denmark)
Dan Witzner Hansen, Technical Univ. of Denmark (Denmark)
Rasmus R. Paulsen, Technical Univ. of Denmark (Denmark)
Rasmus Larsen, Technical Univ. of Denmark (Denmark)

Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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