Abstract

We propose a novel metal artifact reduction (MAR) algorithm for CT images that completes a corrupted sinogram along the metal trace region. When metal implants are located inside a field of view, they create a barrier to the transmitted X-ray beam due to the high attenuation of metals, which significantly degrades the image quality. To fill in the metal trace region efficiently, the proposed algorithm uses multiple prior images with residual error compensation in sinogram space. Multiple prior images are generated by applying a recursive active contour (RAC) segmentation algorithm to the pre-corrected image acquired by MAR with linear interpolation, where the number of prior image is controlled by RAC depending on the object complexity. A sinogram basis is then acquired by forward projection of the prior images. The metal trace region of the original sinogram is replaced by the linearly combined sinogram of the prior images. Then, the additional correction in the metal trace region is performed to compensate the residual errors occurred by non-ideal data acquisition condition. The performance of the proposed MAR algorithm is compared with MAR with linear interpolation and the normalized MAR algorithm using simulated and experimental data. The results show that the proposed algorithm outperforms other MAR algorithms, especially when the object is complex with multiple bone objects.

Highlights

  • Metal artifacts are one of the most common problems in computed tomography (CT)

  • We presented a new metal artifact reduction (MAR) algorithm using multiple prior images with subsequential residual error correction

  • Traditional interpolation-based MAR algorithms replace the metal trace region with neighboring data depending on the distance, which introduces streak artifacts owing to interpolation errors in the metal trace region

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Summary

Introduction

Metal artifacts are one of the most common problems in computed tomography (CT). Various metal implants in the human body such as dental fillings [1], orthopedic implants [2], hip prostheses [3], and implanted marker bins [4], generate dark and bright streaks owing to the high attenuation of metals, which degrade the image quality and diagnostic value of CT images. These are classified into two groups: projection completion methods and iterative methods.

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