中文摘要：

目前,超声图像的配准倍受关注。在MODIFIED HAMMER算法框架的基础上,针对其计算梯度幅值的求导运算在提取超声图像特征时易受斑点噪声影响的问题,基于斑点噪声的统计特性提出了一种新的参数特征用以取代梯度幅值,与LOG算子和灰度值组成特征向量,用于提取超声图像的重要特征点,并完成图像的配准。实验证明,该算法有效减少了重要特征点数目从而减少了配准时间,并且提高了配准精度。

英文摘要：

Ultrasound images registration has attracted more and more attentions nowadays.Due to the speckle noise in ultrasound images,it is difficult to detect features via the calculation of their derivatives.A new parameter feature,which is obtained from the statistical properties of speckle noises,is utilized to replace the gradient amplitude.Firstly the leading points are extracted by feature vectors,which are constructed by the intensity,the Laplacian of the Gaussian and the new parameter feature.Then ultrasound images are registered based on the framework of MODIFIED HAMMER.Experimental results show that the novel method can effectively reduce computational time by cutting down the number of leading points.Besides,registration accuracy is improved.