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Recent CT Metal Artifacts Reduction (MAR) methods are often based onimage-to-image convolutional neural networks for adjustment of corruptedsinograms or images themselves. In this paper, we are exploring thecapabilities of a multi-domain method which consists of both sinogramcorrection (projection domain step) and restored image correction (image-domainstep). Moreover, we propose a formulation of the first step problem as sinograminpainting which allows us to use methods of this specific field such aspartial convolutions. The proposed method allows to achieve state-of-the-art(-75% MSE) improvement in comparison with a classic benchmark - Li-MAR.

Multi-domain CT Metal Artifacts Reduction Using Partial Convolution Based Inpainting