Deep learning techniques have been applied to motion artifact correction without motion estimation or tracking. We previously studied the motion correction method for the multi-contrast brain MRI using NMI maximization and the multi-input neural network. However, as the previous work suffered from a prolonged alignment time and a training inconvenience, we adopt the registration network to reduce alignment time and the multi-output neural network to be trained only once. Our proposed method successfully reduces motion artifacts in the multi contrast images.
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