Optimization of smoothing factor for fast non-local means algorithm in high pitch based low-dose computed tomography images with tin-filter
- Authors
- Seo, Kang-Hyeon; Kang, Seong-Hyeon; Shim, Jina; Lee, Youngjin
- Issue Date
- May-2023
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- Low-dose CT using high pitch; Tin-filter; Noise reduction; Fast non-local means (FNLM) algorithm opti; mization; Quantitative evaluation of image quality
- Citation
- RADIATION PHYSICS AND CHEMISTRY, v.206
- Journal Title
- RADIATION PHYSICS AND CHEMISTRY
- Volume
- 206
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/88326
- DOI
- 10.1016/j.radphyschem.2023.110762
- ISSN
- 0969-806X
- Abstract
- In this study, we applied the fast non-local means (FNLM) algorithm to high-pitch low-dose computed tomography (CT) images using a tin-filter. This study was conducted via a simulation study using a Shepp-Logan phantom and an experimental approach using American association of physicists in medicine (AAPM) phantom images. To optimize the smoothing factor of the FNLM algorithm, the values were adjusted from 0.01 to 0.05 at intervals of 0.001 and applied to the CT image. The smoothing factor of the optimal FNLM algorithm, derived through various quantitative evaluations, was 0.03. According to the results, when the optimized FNLM algorithm was applied to the acquired CT image with a low-dose protocol based on a high pitch condition, the estimated coefficient of variation, contrast-to-noise ratio, and signal-to-noise ratio were improved by 8.7, 6.7, and 8.0 times, respectively, compared to the general CT scanning condition (none). In addition, compared with the noise filtering methods mainly used in the past, both simulation and real experimental results proved that the application efficiency of the FNLM algorithm was high in the obtained low-dose-based CT images. In summary, the applicability of the FNLM algorithm in CT images obtained under low-dose conditions with high pitch using a tin-filter was demonstrated, and the derived research results are expected to be actively utilized in the diagnostic medical field to help reduce exposure doses and improve image quality.
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