【摘要】 基于互信息的医学图像配准算法中,传统的部分体积插值法(PV)使互信息函数在像素整数倍位移处产生局部极值,使优化算法陷于局部最优解,从而导致错误配准。提出用Blackman-Harris窗sinc函数作为核函数,对传统PV插值法进行改进,同时将参与插值的邻域点从4个增加到16个,有效消除了局部极值,得到了光滑的互信息函数曲线。具体配准实验证明,该方法可行,且有更高的鲁棒性。更多还原

【Abstract】 In algorithm of medical image registration based on Mutual Information(MI),when the translation component is integer times of pixel size,conventional PV(Partial Volume) interpolation method will result in the emergency of the local extremes in mutual information registration function,which may hamper the optimization algorithm from getting accurate match parameters.An improved PV interpolation method is proposed by using Blackman-Harris windowed sinc function as kernel function.In addition,the number of concerned neighborhood pixels increases to 16 from 4.Local extremes are eliminated effectively and smooth MI function curve is acquired.The experiments show that the new method is feasible and has higher robustness.更多还原