Surface-based matching using elastic transformations
We introduce a methodology for the alignment of multidimensional data, such as brain scans. The proposed approach does not require fiducial-point correspondence; correspondence of surfaces provides sufficient data for registration. We extend multidimensional interpolation theory by using a more general form of energy functional, which leads to basis functions that have different orders at zero and infinity. This allows flexibility in the design of the interpolation solution. The problem is transformed into a linear algebra problem. Two techniques for better conditioning of the system matrix are described. Experimental results on two- and three-dimensional alignment of brain data used in neurochemistry research are shown. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
energy functional multivariate interpolation solution thin-plate splines preconditioning radial basis functions surface-based alignment