An adaptive stochastic optimization method for medical registration problem

• Autorzy: Król Z.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a methodology that addresses important issues concerned with the optimization of the misregistration measures in the volumetric medical data registration problem. Our registration framework uses robust simulated annealing method to handle multiple local minima of the cost function. Our efforts have been centred on obtaining a reliable, efficient and generally applicable method to solve such optimization problems. This has been accomplished through developing an adaptive cooling schedule for the simulated annealing method. The proposed method is very reliable for the estimation of the global minimum in the optimization of objective functions with highly differentiated search space landscapes. We present the detailed description of the method as well as discussion of its advantages and disadvantages.

Słowa kluczowe

EN

registration; matching; optimization; simulated annealing; similarity measure; non-deterministic methods; cooling schedule; tomographic data

PL

rejestracja; optymalizacja; wyżarzanie; miara podobieństwa; metody niedeterministyczne; chłodzenie; dane tomograficzne

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2004
• Tom: Vol. 7
• Strony: MIP79--88
• Opis fizyczny: Bibliogr. 11 poz., rys.

Twórcy

autor

Król Z.

• Modeling Group, CAESAR – Centre of Advanced European Studies And Research, Ludwig – Erhard –Allee 2, 53175 Bonn, Germany

Bibliografia

• [1] VAN LAARHOVEN P.J.M., AARTS E.H.J., Simulated Annealing: Theory and Applications. Series: Mathematics and its applications. D. Reidel Publishing Company, Dordrecht, 1987.
• [2] KIRKPATRICK S., GELATT JR C.D., VECCHI M.P., Optimization by simulated annealing, Science, 220 (4568), pp. 671-680, 1983.
• [3] ČERNY V., Thermodynamical approach to the travelling salesman problem: An efficient simulation algorithm, Journal of Optimisation Theory and Applications, Vol. 45, pp. 41-51, 1985.
• [4] AZENCOTT R., Simulated annealing - parallelization techniques, John Wiley and Sons, Inc., New York, 1992.
• [5] HUANG M.D., ROMEO F., SANGIOVANNI-VINCENTELLI A.L., An efficient general cooling schedule for simulated annealing, In IEEE International Conference on Computer Aided Design, pp. 381-384, 1986.
• [6] OTTEN R., VAN GINNEKEN L., The Annealing Algorithm, Kluwer Academic Publishers, 1989.
• [7] SECHEN C., VLSI Placement and Global Routing Using Simulated Annealing, Series in Engineering and Computer Science, 54. Kluwer Academic Publishers, 1988.
• [8] RODRIGUES R., BATEL ANJO A., On Simulating Thermodynamics, Applied Simulated Annealing, Ed. by René V. V. Vidal, Lecture Notes in Economics and Mathematical Systems, Vol. 396, pp. 45-60, Springer-Verlag, 1993.
• [9] PRESS W.H., FLANNERY B.P., TEUKOLSKY S.A., VETTERLING W.T., Numerical Recipes in C, Cambridge University Press, second edition, 1992.
• [10] MICHALEWICZ Z., Genetic algorithms + data structures = evolution programs (3rd ed.), Springer-Verlag, London, 1996.
• [11] LUCK J., LITTLE C., HOFF W., Registration of Range Data Using a Hybrid Simulated Annealing and Iterative Closest Point Algorithm, Proc. of IEEE International Conference on Robotics and Automation, San Francisco, April 24-28, 2000.