医学图像配准中的数据抽样方法研究  

Data subsampling in medical image registration

作　　者：胡顺波[1] 刘常春[1] 

机构地区：[1]山东大学控制科学与工程学院

出　　处：《光电子．激光》2008年第2期237-241,共5页Journal of Optoelectronics·Laser

基　　金：国家“863”计划资助项目(2006AA02Z4D9);山东省自然科学基金资助项目(Z2006C05)

摘　　要：针对在基于灰度的医学图像配准中,传统数据抽样方法在过抽样时产生较多的局部极值点问题,提出了基于浮动图像灰度概率分布和其梯度信息的抽样方法。通过对人体脑部的刚体配准实验,从函数曲线和收敛性能方面,对比分析了五种数据抽样方法。实验结果表明,新抽样方法可以有效地减少局部极值点,提高归一化互信息测度的收敛性能。In order to decrease the number of local extrema caused by over subsampling of conventional subsampling methods in intensity-based medical image registration,a new subsampling method based on intensity probability distribution and graclient information of floating image is proposed. The function curves and convergence are compared by applying five subsampling methods to the rigid registration of brain images. The results of tests show that the new subsampling method outperforms other subsampling methods in less extrema and convergence performance of the normalized mutual information.

关 键 词：图像配准 归一化互信息 抽样 

分 类 号：TN911.73[电子电信—通信与信息系统]