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

Artem Pimkin; Alexander Samoylenko; Natalia Antipina; Anna Ovechkina; Andrey Golanov; Alexandra Dalechina; Mikhail Belyaev

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

Computer Vision and Pattern Recognition 2020-05-12 v2

Authors: Artem Pimkin , Alexander Samoylenko , Natalia Antipina , Anna Ovechkina , Andrey Golanov , Alexandra Dalechina , Mikhail Belyaev

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Abstract

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

Keywords

medical image analysis

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@article{arxiv.1911.05530,
  title  = {Multi-domain CT Metal Artifacts Reduction Using Partial Convolution Based Inpainting},
  author = {Artem Pimkin and Alexander Samoylenko and Natalia Antipina and Anna Ovechkina and Andrey Golanov and Alexandra Dalechina and Mikhail Belyaev},
  journal= {arXiv preprint arXiv:1911.05530},
  year   = {2020}
}

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

Abstract

Keywords

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