Robust rigid registration of CT to MRI brain volumes using the SCV similarity measure

Abstract

Multi-modal medical image registration is an important processing step for extracting the maximum amount of information from multi-modal medical images. In this paper, to perform image registration of CT and MRI data volumes, we use the sum-of-conditional variance (SCV) similarity measure which utilizes the joint probability distribution of two images and allows Gauss-Newton optimization to be used. We compare the results from experiments on clinical CT and MRI datasets obtained using the SCV similarity measure, the entropy images on sum-of-squared-difference (eSSD) method and the mutual information (MI) approach. Our results indicate that the proposed SCV approach outperforms the eSSD and MI similarity measure approaches.

DOI: 10.1109/VCIP.2014.7051527

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Cite this paper

@article{Aktar2014RobustRR, title={Robust rigid registration of CT to MRI brain volumes using the SCV similarity measure}, author={Nargis Aktar and Md. Jahangir Alain and Mark R. Pickering}, journal={2014 IEEE Visual Communications and Image Processing Conference}, year={2014}, pages={153-156} }