High-performance medical image registration using new optimization techniques

Optimization of a similarity metric is an essential component in intensity-based medical image registration. The increasing availability of parallel computers makes parallelizing some registration tasks an attractive option to increase speed. In this paper, two new deterministic, derivative-free, and intrinsically parallel optimization methods are adapted for image registration. DIviding RECTangles (DIRECT) is a global technique for linearly bounded problems, and multidirectional search (MDS) is a recent local method. The performance of DIRECT, MDS, and hybrid methods using a parallel implementation of Powell's method for local refinement, are compared. Experimental results demonstrate that DIRECT and MDS are robust, accurate, and substantially reduce computation time in parallel implementations

[1]  Virginia Torczon,et al.  On the Convergence of the Multidirectional Search Algorithm , 1991, SIAM J. Optim..

[2]  V. J. Torczoit,et al.  Multidirectional search: a direct search algorithm for parallel machines , 1989 .

[3]  Aaron Fenster,et al.  Registration of two‐dimensional cardiac images to preprocedural three‐dimensional images for interventional applications , 2005, Journal of magnetic resonance imaging : JMRI.

[4]  Jacek M. Zurada,et al.  An approach to multimodal biomedical image registration utilizing particle swarm optimization , 2004, IEEE Transactions on Evolutionary Computation.

[5]  Carl Tim Kelley,et al.  Iterative methods for optimization , 1999, Frontiers in applied mathematics.

[6]  William H. Press,et al.  Numerical recipes in C , 2002 .

[7]  Jeffrey Tsao,et al.  Interpolation artifacts in multimodality image registration based on maximization of mutual information , 2003, IEEE Transactions on Medical Imaging.

[8]  Colin Studholme,et al.  An overlap invariant entropy measure of 3D medical image alignment , 1999, Pattern Recognit..

[9]  Paul Suetens,et al.  Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information , 1999, Medical Image Anal..

[10]  A. Evans,et al.  MRI simulation-based evaluation of image-processing and classification methods , 1999, IEEE Transactions on Medical Imaging.

[11]  Ponnada A Narayana,et al.  Global optimization of mutual information: application to three-dimensional retrospective registration of magnetic resonance images. , 2002, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[12]  Layne T. Watson,et al.  A Fully Distribute Parallel Global Search Algorithm , 2001, PPSC.

[13]  Stephen M. Smith,et al.  A global optimisation method for robust affine registration of brain images , 2001, Medical Image Anal..

[14]  Torsten Rohlfing,et al.  Nonrigid image registration in shared-memory multiprocessor environments with application to brains, breasts, and bees , 2003, IEEE Transactions on Information Technology in Biomedicine.

[15]  John E. Dennis,et al.  Direct Search Methods on Parallel Machines , 1991, SIAM J. Optim..

[16]  Janusz S. Kowalik,et al.  Iterative methods for nonlinear optimization problems , 1972 .

[17]  John E. Dennis,et al.  Multidirectional search: a direct search algorithm for parallel machines , 1989 .

[18]  Terry M. Peters,et al.  Parallel Optimization Approaches for Medical Image Registration , 2004, MICCAI.

[19]  C. T. Kelley,et al.  A Locally-Biased form of the DIRECT Algorithm , 2001, J. Glob. Optim..

[20]  Terry M. Peters,et al.  Validation of dynamic heart models obtained using non-linear registration for virtual reality training, planning, and guidance of minimally invasive cardiac surgeries , 2004, Medical Image Anal..

[21]  Max A. Viergever,et al.  Mutual-information-based registration of medical images: a survey , 2003, IEEE Transactions on Medical Imaging.

[22]  Tamara G. Kolda,et al.  Optimization by Direct Search: New Perspectives on Some Classical and Modern Methods , 2003, SIAM Rev..

[23]  C. D. Perttunen,et al.  Lipschitzian optimization without the Lipschitz constant , 1993 .

[24]  Konstantina S. Nikita,et al.  Automatic retinal image registration scheme using global optimization techniques , 1999, IEEE Transactions on Information Technology in Biomedicine.

[25]  N.P. Castellanos,et al.  Nonrigid medical image registration technique as a composition of local warpings , 2004, Pattern Recognit..

[26]  Paul A. Viola,et al.  Multi-modal volume registration by maximization of mutual information , 1996, Medical Image Anal..

[27]  Pramod K. Varshney,et al.  Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation , 2003, IEEE Transactions on Medical Imaging.

[28]  Terry M. Peters,et al.  Multiresolution Biomedical Image Registration Using Generalized Information Measures , 2003, MICCAI.

[29]  K. I. M. McKinnon,et al.  Convergence of the Nelder-Mead Simplex Method to a Nonstationary Point , 1998, SIAM J. Optim..

[30]  Ron Kikinis,et al.  A High Performance Computing Approach to the Registration of Medical Imaging Data , 1998, Parallel Comput..

[31]  Guy Marchal,et al.  Multimodality image registration by maximization of mutual information , 1997, IEEE Transactions on Medical Imaging.

[32]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .