Voxel similarity measures for automated image registration

Derek L.G. Hill; Colin Studholme; David John Hawkes

doi:10.1117/12.185180

9 September 1994 Voxel similarity measures for automated image registration

Derek L.G. Hill, Colin Studholme, David John Hawkes

Proceedings Volume 2359, Visualization in Biomedical Computing 1994; (1994) https://doi.org/10.1117/12.185180
Event: Visualization in Biomedical Computing 1994, 1994, Rochester, MN, United States

Abstract

We present the concept of the feature space sequence: 2D distributions of voxel features of two images generated at registration and a sequence of misregistrations. We provide an explanation of the structure seen in these images. Feature space sequences have been generated for a pair of MR image volumes identical apart from the addition of Gaussian noise to one, MR image volumes with and without Gadolinium enhancement, MR and PET-FDG image volumes and MR and CT image volumes, all of the head. The structure seen in the feature space sequences was used to devise two new measures of similarity which in turn were used to produce plots of cost versus misregistration for the 6 degrees of freedom of rigid body motion. One of these, the third order moment of the feature space histogram, was used to register the MR image volumes with and without Gadolinium enhancement. These techniques have the potential for registration accuracy to within a small fraction of a voxel or resolution element and therefore interpolation errors in image transformation can be the dominant source of error in subtracted images. We present a method for removing these errors using sinc interpolation and show how interpolation errors can be reduced by over two orders of magnitude.

Citation Download Citation

Derek L.G. Hill, Colin Studholme, and David John Hawkes "Voxel similarity measures for automated image registration", Proc. SPIE 2359, Visualization in Biomedical Computing 1994, (9 September 1994); https://doi.org/10.1117/12.185180

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