Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Block-matching and 3D filtering algorithm in X-ray image with photon counting detector using the improved K-edge subtraction method

  • Kyuseok Kim (Department of Biomedical Engineering, Eulji University) ;
  • Youngjin Lee (Department of Radiological Science, Gachon University)
  • Received : 2023.07.17
  • Accepted : 2024.01.09
  • Published : 2024.06.25
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Abstract

Among photon counting detector (PCD)-based technologies, the K-edge subtraction (KES) method has a very high material decomposition efficiency. Yet, since the increase in noise in the X-ray image to which the KES method is applied is inevitable, research on image quality improvement is essential. Here, we modeled a block-matching and 3D filtering (BM3D) algorithm and applied it to PCD-based X-ray images with the improved KES (IKES) method. For PCD modeling, Monte Carlo simulation was used, and a phantom composed of iodine substances with different concentrations was designed. The IKES method was modeled by adding a log term to KES, and the X-ray image used for subtraction was obtained by applying the 3.0 keV range based on the K-edge region of iodine. As a result, the IKES image using the BM3D algorithm showed the lowest normalized noise power spectrum value. In addition, we confirmed that the contrast-to-noise ratio and no-reference-based evaluation results when the BM3D algorithm was applied to the IKES image were improved by 29.36 % and 20.56 %, respectively, compared to the noisy image. In conclusion, we demonstrated that the IKES imaging technique using a PCD-based detector and the BM3D algorithm fusion technique were very efficient for X-ray imaging.

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References

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