Image restoration of medical images with streaking artifacts by Euler's elastica inpainting

Streaking artifacts caused by metallic objects severely affect the visual quality of CT images, resulting in medical misdiagnosis. Commonly used approaches for metal artifact reduction usually consist of interpolation and iterative methods. The former one tends to lose image quality by introducing extra artifacts, while the latter is more computational expensive. This paper proposes a new approach based on the Euler's elastica inpainting technique, which can preserve sharp edges and curvature when reconstructing the sinogram image, resulting in better quality in the restored CT image. Results of quantitative and qualitative experiments on both simulated phantoms and clinical CT images demonstrate that our method can suppress metal artifacts significantly.