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A Dual-domain Regularization Method for Ring Artifact Removal of X-ray CT

Hongyang Zhu, Xin Lu, Yanwei Qin, Xinran Yu, Tianjiao Sun, Yunsong Zhao

Abstract

Ring artifacts in computed tomography images, arising from the undesirable responses of detector units, significantly degrade image quality and diagnostic reliability. To address this challenge, we propose a dual-domain regularization model to effectively remove ring artifacts, while maintaining the integrity of the original CT image. The proposed model corrects the vertical stripe artifacts on the sinogram by innovatively updating the response inconsistency compensation coefficients of detector units, which is achieved by employing the group sparse constraint and the projection-view direction sparse constraint on the stripe artifacts. Simultaneously, we apply the sparse constraint on the reconstructed image to further rectified ring artifacts in the image domain. The key advantage of the proposed method lies in considering the relationship between the response inconsistency compensation coefficients of the detector units and the projection views, which enables a more accurate correction of the response of the detector units. An alternating minimization method is designed to solve the model. Comparative experiments on real photon counting detector data demonstrate that the proposed method not only surpasses existing methods in removing ring artifacts but also excels in preserving structural details and image fidelity.

A Dual-domain Regularization Method for Ring Artifact Removal of X-ray CT

Abstract

Ring artifacts in computed tomography images, arising from the undesirable responses of detector units, significantly degrade image quality and diagnostic reliability. To address this challenge, we propose a dual-domain regularization model to effectively remove ring artifacts, while maintaining the integrity of the original CT image. The proposed model corrects the vertical stripe artifacts on the sinogram by innovatively updating the response inconsistency compensation coefficients of detector units, which is achieved by employing the group sparse constraint and the projection-view direction sparse constraint on the stripe artifacts. Simultaneously, we apply the sparse constraint on the reconstructed image to further rectified ring artifacts in the image domain. The key advantage of the proposed method lies in considering the relationship between the response inconsistency compensation coefficients of the detector units and the projection views, which enables a more accurate correction of the response of the detector units. An alternating minimization method is designed to solve the model. Comparative experiments on real photon counting detector data demonstrate that the proposed method not only surpasses existing methods in removing ring artifacts but also excels in preserving structural details and image fidelity.
Paper Structure (14 sections, 22 equations, 5 figures, 1 table, 1 algorithm)

This paper contains 14 sections, 22 equations, 5 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Materials and methods
  3. Formulation for Ring Artifact Removal
  4. Related methods
  5. The proposed optimization model
  6. The projection domain regularization term ${R}_{P}\left(\boldsymbol{S}\right)$
  7. The image domain regularization term ${R}_{I}\left(\boldsymbol{x}\right)$
  8. Numerical implementation
  9. Experiments
  10. Results
  11. The results of the water-and-bone sample
  12. The results of the pork-with-bone sample
  13. Discussion
  14. Conclusion

Figures (5)

  • Figure 1: The photograph of two scanned samples. (a) The water-and-bone sample. (b) The pork-with-bone sample.
  • Figure 2: The experimental CT platform.
  • Figure 3: The reconstruction results of the water-and-bone sample. (a) Uncorrected image; (b) WF method; (c) Podgorsak method; (d) Wu method; (e) Salehjahromi method; (f) The proposed method. The display window is set to [0, 0.1].
  • Figure 4: The reconstruction results of the pork-with-bone sample. (a) Uncorrected image; (b) WF method; (c) Podgorsak method; (d) Wu method; (e) Salehjahromi method; (f) The proposed method. The display window is set to [0, 0.08].
  • Figure 5: The uncorrected sinogram of two samples. (a) The uncorrected sinogram of the water-and-bone sample. (b) The uncorrected sinogram of the pork-with-bone sample.