Abstract

Image registration is regarded as an important component of medical procedures. The present study aimed to introduce a new transformation model based on dual-tree complex wavelet transform (DT-CWT). To this aim, parametric registration methods was revised based on the function expansion theory and the gradient descent algorithm was used to introduce a general formulation for transformation models based on spatio-spectral transforms. Then, the performance of the proposed method was evaluated on a public dataset of 3D real magnetic resonance images (MRI) and compared with the transformation model based on wavelets. Finally, the performance of the proposed method was compared with the current state-of-the-art methods (IRTK, SyN and SPM-DARTEL). Based on the experimental results, the proposed method could deliver superior registration performance compared with the previous methods.

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