Efficient convolution-based pairwise elastic image registration on three multimodal similarity metrics

•Convolutional formulation for 2D multimodal pairwise image registration problems based on the free-form deformation paradigm.•The proposed method uses simple 1D convolution operations instead of the classical implementation based on tensor products, leading to a large reduction in runtime.•The convolutional approach is adapted to three different multimodal metrics, namely, normalized cross correlation, mutual information and normalized mutual information. Moreover, a sufficient condition on the gradient of metric is provided for further extension to other metrics.•Reformulated functions are the spatial transformation, the regularization term, as well as the corresponding gradient functions; all of these are evaluated at each iteration of the optimization process during the image registration procedure.