PMID: 16617623Apr 19, 2006Paper

High-performance medical image registration using new optimization techniques

IEEE Transactions on Information Technology in Biomedicine : a Publication of the IEEE Engineering in Medicine and Biology Society
Mark P Wachowiak, T M Peters

Abstract

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.

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Citations

Feb 6, 2007·Journal of Nuclear Cardiology : Official Publication of the American Society of Nuclear Cardiology·Anu JuslinUlla Ruotsalainen
May 4, 2004·Computers in Biology and Medicine·Renata SmolíkováJ M Jacek M Zurada
May 9, 2014·IEEE Journal of Biomedical and Health Informatics·Kei IkedaKenichi Hagihara
Jan 1, 2008·IEEE Transactions on Medical Imaging·Xishi HuangTerry M Peters
Jul 11, 2006·Physics in Medicine and Biology·Terry M Peters

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