Parallel optimization approaches for medical image registration

Abstract

Optimization of a similarity metric is an essential component in most medical image registration approaches based on image intensities. The increasing availability of parallel computers makes parallelizing some registration tasks an attractive option. In this paper, two relatively new, deterministic, direct optimization algorithms are parallelized for distributed memory systems, and adapted for image registration. DIRECT is a global technique, and the multidirectional search is a recent local method. The performance of several variants are compared. Experimental results show that both methods are robust, accurate, and, in parallel implementations, can significantly reduce computation time. © Springer-Verlag Berlin Heidelberg 2004.