A new correlation ratio similarity measure for voxel intensity based medical image registration was adopted in the registration system design.
在基于体素灰度的医学图像配准领域 ,采用全新的相关比相似性测度作为配准的测度准则 ,对多分辨率加速配准方案中涉及的几何变换选取、重采样、多分辨率体数据表达及最优化方法进行了设计分析 。
Method Under extreme rigid registration condition, correlation coefficient,mutual information and correlation ratio similarity measures were tested as most suitable similarity measures.
方法在极端的刚体配准条件下 ,检验出互相关系数 ,互信息和相关比相似性测度为适合的相似性测度。
Under the extreme registration condition, the mutual information, normalized mutual information, correlation ratio are considered as most suitable similarity measures.
对基于体素灰度多模医学图像配准中广泛采用的相似性测度 (SM)进行了比较研究 ,认为在配准条件极不理想的条件下 ,基于互信息 (SM)、归一化互信息 SN、相关比 (SR)的 SM是最为适用的 。
