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A CT metal artifact reduction algorithm based on sinogram surgery.

Soomin Jeon1, Chang-Ock Lee1

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|March 23, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm to reduce streak artifacts in computed tomography (CT) images caused by metal implants. The novel method, sinogram surgery, effectively minimizes artifacts without introducing new ones, improving image quality.

Keywords:
Computed tomography (CT)iterative algorithmmetal artifact reductionsinogram surgery

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Area of Science:

  • Medical Imaging
  • Image Processing
  • Computational Science

Background:

  • Streak artifacts in computed tomography (CT) images arise from metallic objects, hindering diagnostic accuracy.
  • Existing artifact reduction methods often introduce new artifacts or fail to completely remove them.

Purpose of the Study:

  • To propose a novel algorithm for reducing streak artifacts in CT images.
  • To address the limitations of current metal artifact reduction techniques.

Main Methods:

  • A new algorithm is proposed that identifies metal components (M) and surrounding areas (C) in CT images.
  • The algorithm replaces the metal and surrounding area with an average CT number and uses sinogram surgery to remove metallic effects.

Main Results:

  • Numerical experiments with simulated phantoms and patient images demonstrated significant artifact reduction.
  • The algorithm reduced l∞ errors by a factor of 20 and l2 errors by less than 5% in patient image simulations.
  • Simulated phantom experiments showed l∞ and l2 errors approaching 10% and 1% of initial errors, respectively.

Conclusions:

  • The proposed metal artifact reduction algorithm effectively reduces artifacts without generating additional ones.
  • The algorithm's empirical convergence is demonstrated, offering a reliable solution for metal artifact issues in CT imaging.