Rigid registration of CT, MR and cryosection images using a GLCM framework

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 co-occurrence 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. This paper discusses existing and some new voxel similarity measures for image registration.

Elaborate tests are used to evaluate the different measures and compare them. Finally, a registration algorithm based on voxel similarity measures is described and some results are presented