摘要
基于互信息的医学图像配准,其配准精度可以达到亚像素水平,精度高且鲁棒性好,但互信息的巨大计算量使配准速度较慢,不能达到临床使用要求,而互信息的计算速度与图像的灰度阶数有关。为此,针对互信息由于图像灰度级数过多造成互信息计算量大的问题,提出一种基于图像梯度的灰度压缩算法。算法采用图像的梯度信息,根据图像梯度对图像进行非线性灰度映射,同时利用小波对差异图像进行分解和重构。实验结果证明,该算法能减少图像灰度阶数,同时较好地保留图像的细节信息,在保持配准精度的前提下减少配准时间。
The accuracy of medical image registration based on mutual information can reach sub-pixel level,with high accuracy and good robustness.However,frequent involving a huge amount of floating-point calculation,the rate of registration is very slow and can not achieve real-time requirements of clinical use.Because the rate of mutual information is relative to the amount of gray-scales,this paper presents a method based on a nonlinear grayscale mapping method which uses the gradient information of the image.A different image is decomposited and recomposited by a wavelet.Experimental result shows the method can reduce the gray scale of a image at the premise of preserving the image details.Moreover,this algorithm reduces the registration time and maintain the accuracy of registration.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第7期237-240,共4页
Computer Engineering
关键词
灰度压缩
梯度
医学图像配准
grayscale compression
gradient
medical image registration
