基于混合互信息和改进粒子群优化算法的医学图像配准方法

doi:doi: 10.3969/j.issn.0258-8021.2015.01.001

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Abstract A novel medical image registration method based on mixed mutual information and improved particle swarm optimization algorithm was proposed. During each iteration of the proposed algorithm, the improved particle swarm optimization algorithm based on Renyi’s entropy was adopted firstly in global searching phase. Then the mutual information measure based on Shannon’s entropy was taken as the objective function while the Powell algorithm was used to obtain the optimal solution in local searching phase. The monomodality medical image registration accuracy including sixty simulated images and ten clinical medical images is improved to subpixel level by the proposed algorithm. Comparing with the other three algorithms in the experiment of multimodality medical image registration, the quality of the registered image was evaluated by five kinds of objective criterions, the proposed algorithm was optimal for the four object indexes except for computation time, the mean of MI, NMI and CC index was 1.338 6, 1.363 1 and 0.837 8 respectively, subjective and objective analysis of the results showed that the proposed algorithm has the advantage in accuracy and effectiveness over other image registration methods.

Received: 18 March 2015 Published: 18 March 2015

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	Shi Yixin¹ Qiu Tianshuang^1*Han Jun² Jin Sheng³

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Shi Yixin¹ Qiu Tianshuang^1*Han Jun² Jin Sheng³. Medical Image Registration Algorithm Based on Mixed Mutual Information and Improved Particle Swarm Optimization[J]. journal1, 2015, 34(1): 1-7.

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http://cjbme.csbme.org/EN/doi: 10.3969/j.issn.0258-8021.2015.01.001 OR http://cjbme.csbme.org/EN/Y2015/V34/I1/1

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