A Comparative Study of Bio-inspired Algorithms for Medical Image Registration
The challenge of determining optimal transformation parameters for image registration has been treated traditionally as a multidimensional optimization problem. Non-rigid registration of medical images has been approached in this article using the particle swarm optimization algorithm, dragonfly algorithm, and the artificial bee colony algorithm. Brief introductions to these algorithms have been presented. Results of MATLAB simulations of medical image registration approached through these algorithms have been analyzed. The simulation shows that the dragonfly algorithm results in higher quality image registration, but takes longer to converge. The trade-off issue between the quality of registration and the computing time has been brought forward. This has a strong impact on the choice of the most suitable algorithm for medical applications, such as monitoring of tumor progression.
KeywordsArtificial bee colony algorithm Dragonfly algorithm Medical image registration Particle swarm optimization algorithm Swarm intelligence
Authors acknowledge with gratitude the support received from REVA University, Bengaluru, and M. S. Ramaiah University of Applied Sciences, Bengaluru. They also express sincere thanks to the anonymous reviewers of this article for their constructive criticism.
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