DL‐based inpainting for metal artifact reduction for cone beam CT using metal path length information
Medical Physics2022Vol. 50(1), pp. 128–141
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Abstract
In this paper, a learning-based inpainting network is proposed that leverages prior knowledge about the metal path length of the inserted implant. Evaluations on real measured data reveal an increased overall MAR performance, especially regarding the preservation of anatomical structures adjacent to the inserted implants. Further evaluations suggest the ability of the proposed approach to generalize to clinical cases.
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