Hybrid corner detection algorithm for brain magnetic resonance image registration

Abstract

Corner detection algorithm is key to the image registration algorithm based on corner feature point. According to the brain magnetic resonance (MR) image registration, this paper proposed a hybrid corner detection algorithm by combining the Harris and Susan operators and applied it into brain MR image registration. Firstly, this method extracts the Harris and Susan corner feature points by using Harris and Susan operators. Secondly, this method merges the points and conducts weight computation based on two weight coefficients ω 1 and ω 2 . After that, the feature points can be chosen further. Through normalization relevance method and voting mechanism, the final feature points are chosen further and are matched between reference image and image needing registration. Finally, the Powell algorithm is used and the final transform coefficients are obtained. The experimental results show that this algorithm can be used for brain MR image registration and can obtain higher registration precision and.