Wachowiak Mark P. High-Performance Medical Image Registration Using New Optimization Techniques [Електронний ресурс] / Mark P. Wachowiak, Terry M. Peters // IEEE Transactions on Information Technology in Biomedicine. – 2006. – № 2. – P. 344 – 353
- Електронна версія (pdf / 675 Kb)
Статистика використання: Завантажень: 3
Анотація:
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.
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.