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A metal artifact reduction scheme in CT by a Poisson fusion sinogram based postprocessing method.

Hui Tang^1,2, Yu Bing Lin¹, Guo Yan Sun¹

¹Laboratory of Image Science and Technology, School of Computer Science and Engineering, Southeast University, Nanjing, China.

Journal of X-Ray Science and Technology

|January 18, 2021

Summary

This summary is machine-generated.

This study introduces a new Poisson fusion sinogram based metal artifact reduction (FS-MAR) method. The FS-MAR method effectively reduces artifacts in CT images, outperforming traditional interpolation-based algorithms.

Keywords:

Computed tomography Poisson blending image fusion metal artifact reduction

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Area of Science:

Medical Imaging
Image Processing
Computational Science

Background:

Current interpolation-based metal artifact reduction (MAR) methods can generate secondary artifacts.
Metal artifacts significantly degrade the quality of CT images, impacting diagnostic accuracy.

Purpose of the Study:

To propose and evaluate a novel Poisson fusion sinogram based metal artifact reduction (FS-MAR) method.
To reduce secondary artifacts and improve image quality in metal-affected CT scans.

Main Methods:

The FS-MAR method involves generating a prior image and using Poisson blending to create a corrected sinogram.
Filtered back projection (FBP) is applied to the corrected sinogram, followed by image reconstruction.
Image quality was assessed using simulated and real clinical data with metrics like SSIM and PSNR.

Main Results:

The FS-MAR method achieved the highest SSIM (0.8912) and PSNR (30.6693) in testing samples.
Visual evaluations confirmed that FS-MAR generates fewer artifacts compared to interpolation-based methods.
Both simulated and clinical images showed superior artifact reduction with FS-MAR.

Conclusions:

The proposed Poisson FS-MAR method demonstrates superior performance in enhancing CT image quality.
FS-MAR provides a significant improvement over interpolation-based algorithms for metal artifact reduction.
This method offers a promising solution for improving diagnostic clarity in the presence of metallic implants.