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This paper presents a rapid algorithm for medical image registration, the purpose is to solve problems, which are the inferiority of low speed and huge calculation in medical images registration based on normal mutual information. We present a two-step search strategy to speed-up registration process according to the different regions between the target image and the source image. In a first step the coarse granularity search determines the limits of target range; between-class distance is used in the initial step for discriminating similarity. In a second step the fine-grained search computes similarity measure by using normalized mutual information to achieve final image registration. Experimental results show that the method, which keeps precision of registration, can solve the problem of low speed, and achieve good effects.