广义信息熵测度在医学图像配准中的应用  

Medical image registration based on generalized entropy measures

作　　者：杨金宝[1] 刘常春[1] 胡顺波[1] 

机构地区：[1]山东大学控制科学与工程学院,济南250061

出　　处：《计算机工程与应用》2008年第8期34-36,52,共4页Computer Engineering and Applications

基　　金：国家高技术研究发展计划( 863)( the National High- Tech Research and Development Plan of China under Grant No.2006AA02Z4D9);山东省自然科学基金( the Natural Science Foundation of Shandong Province of China under Grant No.Z2006C05)

摘　　要：针对互信息测度在配准医学图像时易陷入局部极值的缺点,将Shannon熵扩展到广义熵,提出了三种基于广义熵的信息测度。对于收敛性能的评价,提出收敛宽度和收敛半径的概念。通过人体脑部CT/MR和MR-T1/T2图像的刚体配准实验,从计算时间、收敛性能和配准精度方面,对归一化互信息、广义熵信息测度进行了比较与分析。实验结果表明,在不损失计算时间和配准精度的前提下,广义信息熵测度SRI_0.9和GMI_0.9的收敛性能优于归一化互信息测度,对噪声有很强的鲁棒性。In order to reduce local maximum and misregistration of mutual information in medical image registration,three information measures based on generalized entropy instead of the Shannon entropy,named as FRI-alpha,SRI-alpha and GMI-t information measures,are proposed.The convergence width and radius are used for evaluating the measure convergence.The computing time,convergence and accuracy are studied by applying these measures to rigid registration of Computed Tomography（CT）/Magnetic Resonance（MR） and MR-T1/T2 simulated images.The results of tests show that the generalized entropy measures outperform normalized mutual information in convergence performance,without compromising computational speed and registration accuracy.

关 键 词：Shannon熵 互信息 广义熵 图像配准 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]