Task-specific comparison of 3-D image registration methods

We present a new class of approaches for rigid-body registration and their evaluation in studying Multiple Sclerosis via multi protocol MRI. Two pairs of rigid-body registration algorithms were implemented, using cross-correlation and mutual information, operating on original gray-level images and on the intermediate images resulting from our new scale-based method. In the scale image, every voxel has the local "scale" value assigned to it defined as the radius of the largest sphere centered at the voxel with homogeneous intensities. 3D data of the head were acquired from 10 MS patients using 6 MRI protocols. Images in some of the protocols have been acquired in registration. The co-registered pairs were, used as ground truth., Accuracy and consistency of the 4 registration methods were measured within and between protocols for known amounts of misregistrations. Our analysis indicates that there is no "best" method. For medium and large misregistration, methods using mutual information, for small misregistration, and for the consistency tests, correlation methods using the original gray-level images give the best results. Wa have, previously demonstrated the use of local scale information in fuzzy connectedness segmentation and image filtering. Scale may also have considerable potential for image registration as suggested by this work.