Spatial distribution of residual error in 3D image coregistration: An experimental study
This paper analyzes the spatial distribution of residual error resulting from resulting from 3D image coregistration algorithms which use rigid body transformations. The large number of applications in diagnostic and surgical imaging are increasingly using coregistration to follow subtle changes in size and shape of anatomical structures and lesions. This adoption of coregistration techniques requires a better understanding of their physical properties. Our study involved applying a known 3D transformation to digital phantoms with special identifiable markers on a lattice. The resulting transformed image was then processed to uniquely identify the special markers in both the original image and the transformed image so that the error distribution could be computed. The identification of landmarks was made possible by reformatting the 3D image without performing gray level interpolation. Since the special markers could each be uniquely identified in the 3D space, error distances could also be measured throughout the image and expressed as a function of the distance from the center of the image. The results provide us with empirical evidence that errors within the interior of a 3D image volume are on the average smaller than errors measured at the surface. The empirical results clarify the properties of the spatial distribution of registration errors and hopefully can be used to guide future studies that evaluate the accuracy of image registration techniques.