Metallic Artifacts’ Reduction in Microtomography Using the Bone- and Soft-Tissue Decomposition Method

Artifacts in computed tomography and X-ray microtomography are image distortions caused by various factors. Some can be reduced before or during the examination, while others are removed algorithmically after image acquisition. The latter group includes metallic artifacts caused by metal objects in the sample. This paper proposes a new method for eliminating metallic artifacts, applying a bone- and soft-tissue decomposition (BSTD) algorithm to microtomography raw data before the reconstruction process. We show that the decomposition algorithm can effectively remove metallic artifacts in microCT images, which increases the image contrast and allows for better visualization of regions near the metallic elements. For quantity analysis, we computed SSIM and PSNR factors, and we observed values increasing from 0.97 to 0.99 and from 40 dB to 43 dB, respectively.

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Publication Details

Journal
Sensors
Published
2024-11-05
DOI
https://doi.org/10.3390/s24227108
Primary Topic
Advanced X-ray and CT Imaging
Type
article
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article

Metallic Artifacts’ Reduction in Microtomography Using the Bone- and Soft-Tissue Decomposition Method

Ewa Piętka, Jan Juszczyk, Jakub Pałachniak
Sensors
Advanced X-ray and CT Imaging
article

Metallic Artifacts’ Reduction in Microtomography Using the Bone- and Soft-Tissue Decomposition Method

Ewa Piętka, Jan Juszczyk, Jakub Pałachniak
article en

Abstract

Artifacts in computed tomography and X-ray microtomography are image distortions caused by various factors. Some can be reduced before or during the examination, while others are removed algorithmically after image acquisition. The latter group includes metallic artifacts caused by metal objects in the sample. This paper proposes a new method for eliminating metallic artifacts, applying a bone- and soft-tissue decomposition (BSTD) algorithm to microtomography raw data before the reconstruction process. We show that the decomposition algorithm can effectively remove metallic artifacts in microCT images, which increases the image contrast and allows for better visualization of regions near the metallic elements. For quantity analysis, we computed SSIM and PSNR factors, and we observed values increasing from 0.97 to 0.99 and from 40 dB to 43 dB, respectively.

SensorsVol. 24(22)
Silesian University of Technology (PL), Institute of Medical Technology and Equipment (PL)
Openalex Percentile: Top 82%
Advanced X-ray and CT Imaging
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