Abstract
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.
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© 1997 Springer-Verlag Berlin Heidelberg
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Bro-Nielsen, M. (1997). Rigid registration of CT, MR and cryosection images using a GLCM framework. In: Troccaz, J., Grimson, E., Mösges, R. (eds) CVRMed-MRCAS'97. CVRMed MRCAS 1997 1997. Lecture Notes in Computer Science, vol 1205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029236
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DOI: https://doi.org/10.1007/BFb0029236
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