Robust registration for change detection

Sune Darkner; Dan Witzner Hansen; Rasmus R. Paulsen; Rasmus Larsen

doi:10.1117/12.770106

26 March 2008 Robust registration for change detection

Sune Darkner, Dan Witzner Hansen, Rasmus R. Paulsen, Rasmus Larsen

Proceedings Volume 6914, Medical Imaging 2008: Image Processing; 69142T (2008) https://doi.org/10.1117/12.770106
Event: Medical Imaging, 2008, San Diego, California, United States

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.

Citation Download Citation

Sune Darkner, Dan Witzner Hansen, Rasmus R. Paulsen, and Rasmus Larsen "Robust registration for change detection", Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69142T (26 March 2008); https://doi.org/10.1117/12.770106

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available