Rigid registration of CT, MR and cryosection images using a GLCM framework
Rigid registration of CT, MR and cryosection images using a GLCM framework
复制标题
DOI：
10.1007/bfb0029236
复制
发表时间：
1997-01-01
期刊：
影响因子：
--
通讯作者：
BroNielsen, M
中科院分区：
文献类型：
--
作者：
BroNielsen, M
大多数可用的刚性配准措施都是基于配准图像中相应灰度值的二维直方图。本文表明，这些特征类似于基于灰度共生矩阵（GLCM）的一系列纹理度量。将 GLCM 文献中的特征与使用可见人类数据集中的图像的当前测量范围进行比较。基于体素的冷冻切片和 CT 图像的刚性配准以前没有报道过。测试表明，互信息是最好的一般度量，但某些 GLCM 特征对于特定模态组合更好。
The majority of the available rigid registration measures are based on a 2-dimensional histogram of corresponding grey-values in the registered images. This paper shows that these features are similar to a family of texture measures based on Grey Level Cooccurrence Matrices (GLCM). Features from the GLCM literature are compared to the current range of measures using images from the visible human data set. The voxel-based rigid registration of Cryosection and CT images have not been reported before. The tests show that mutual information is the best general measure, but some GLCM features are better for specific modality combinations.