3D Head and Neck CT/MR Registration Method Based on Local Normalized Mutual Information Joint Constraint
An improved multimodal registration method is proposed for the complex anatomical struc-ture of head and neck images and the differences of different modal images.This method uses local normal-ized mutual information as a similarity measure to capture the similarity of local image regions and reduce the influence of intensity differences between different regions on the registration results.In addition,in or-der to solve the problem that MR images are susceptible to distortion caused by noise and artifacts,we in-troduce an F-norm constrained registration process to suppress unnecessary distortion.Experimental re-sults show that the proposed method improves the mean squared error,the registration accuracy and ro-bustness.
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