Ring artifacts correction in compressed sensing tomographic reconstruction.

Area of Science:

• Medical Imaging
• Computational Science
• Physics

Background:

• Ring artifacts are a pervasive issue in tomographic reconstruction, degrading image quality.
• Existing methods involve pre-processing sinograms or post-reconstruction slice correction.
• These methods can be complex and may not fully resolve artifacts, especially in challenging datasets.

Purpose of the Study:

• To develop and evaluate a novel method for simultaneous tomographic reconstruction and ring artifact correction.
• To integrate ring artifact correction directly into iterative reconstruction algorithms.
• To compare the proposed method against established correction techniques.

Main Methods:

• A novel approach integrating ring artifact correction into the objective function optimization of iterative reconstruction techniques.
• Testing the method on both simulated and experimental tomographic datasets.
• Comparison with mainstream pre-processing and post-correction methods.

Main Results:

• The integrated method effectively corrects ring artifacts during the reconstruction process.
• The technique demonstrates particular efficiency when applied to undersampled datasets.
• Performance is validated against conventional correction strategies.

Conclusions:

• Simultaneous reconstruction and ring artifact correction is feasible and efficient within iterative frameworks.
• This integrated approach offers an advantage, especially for undersampled tomographic data.
• The developed technique has been implemented in the PyHST2 code for practical application at facilities like the European Synchrotron Radiation Facility.