Abstract
Because of the drift which exists in sequence image of prostate DWI (Diffusion Weighted Imaging), the global ant colony algorithm is introduced into the paper for registration optimization. The paper introduces an ant colony algorithm for continuous function optimization, based on max-min ant system (MMAS). This paper controls the transition probabilities and enhances the abilities of ants seeking globally optimal solutions by adding an adjustable factor in the basic ant colony algorithm and updating the local pheromone and global pheromone. Experimental results verify the effectiveness of the algorithm.
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