Preview
Sign-in for full Details 
Sign-in free and Explore the Exciting World of BiomedExperts:
- Over 1,800,000 Profiles
- More than 3,500 Organizations worldwide
- State of the Art Network Visualizations
- Manage your own Profile
- Locate Experts in your Country/Region
- Locate Experts in your 1. and 2. Level Network
- Connect to Experts Worldwide
find experts for
Sign-in to see more
1999:
Maes F; Vandermeulen D; Suetens P
Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information.
Medical image analysis 1999;
3(
4):.
Maximization of mutual information of voxel intensities has been demonstrated to be a very powerful criterion for three-dimensional medical image registration, allowing robust and accurate fully automated affine registration of multimodal images in a variety of applications, without the need for segmentation or other preprocessing of the images. In this paper, we investigate the performance of various optimization methods and multiresolution strategies for maximization of mutual information, aiming at increasing registration speed when matching large high-resolution images. We show that mutual information is a continuous function of the affine registration parameters when appropriate interpolation is used and we derive analytic expressions of its derivatives that allow numerically exact evaluation of its gradient. Various multiresolution gradient- and non-gradient-based optimization strategies, such as Powell, simplex, steepest-descent, conjugate-gradient, quasi-Newton and Levenberg-Marquardt methods, are evaluated for registration of computed tomography (CT) and magnetic resonance images of the brain. Speed-ups of a factor of 3 on average compared to Powell's method at full resolution are achieved with similar precision and without a loss of robustness with the simplex, conjugate-gradient and Levenberg-Marquardt method using a two-level multiresolution scheme. Large data sets such as 256(2) x 128 MR and 512(2) x 48 CT images can be registered with subvoxel precision in <5 min CPU time on current workstations.
Post to CiteULike 
Sign in free and see...
Visualized networks:
See your personal network in
sophisticated graphical views
GeoTargeted Searches:
Locate experts around the world
and connect with global collaborators
Research Profiles:
See the visualized research activity
of experts around the globe
Sign-in to see more
