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High Performance Derivative-Free Optimization Applied to Biomedical Image Registration
19th International Symposium on High Performance Computing Systems and Applications (HPCS'05)
Optimization of a similarity metric is an essential component in most medical image registration approaches based on image intensities. In this paper, two new, deterministic, derivative-free optimization algorithms are parallelized and adapted for image registration. DIRECT (dividing rectangles) is a global technique for linearly bounded problems, and the multidirectional search (MDS) is a local method. Unlike many other deterministic optimization techniques, DIRECT and MDS allow coarse-grained
doi:10.1109/hpcs.2005.31
dblp:conf/hpcs/WachowiakP05
fatcat:l2quohhywnf2lfxqzpd54kec24