Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Experimental study of noise level optimization in brain single-photon emission computed tomography images using non-local means approach with various reconstruction methods

  • Seong-Hyeon Kang (Department of Health Science, General Graduate School of Gachon University) ;
  • Seungwan Lee (Department of Radiological Science, Konyang University) ;
  • Youngjin Lee (Department of Radiological Science, College of Health Science, Gachon University)
  • Received : 2022.10.11
  • Accepted : 2023.01.15
  • Published : 2023.05.25
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Abstract

The noise reduction algorithm using the non-local means (NLM) approach is very efficient in nuclear medicine imaging. In this study, the applicability of the NLM noise reduction algorithm in single-photon emission computed tomography (SPECT) images with a brain phantom and the optimization of the NLM algorithm by changing the smoothing factors according to various reconstruction methods are investigated. Brain phantom images were reconstructed using filtered back projection (FBP) and ordered subset expectation maximization (OSEM). The smoothing factor of the NLM noise reduction algorithm determined the optimal coefficient of variation (COV) and contrast-to-noise ratio (CNR) results at a value of 0.020 in the FBP and OSEM reconstruction methods. We confirmed that the FBP- and OSEM-based SPECT images using the algorithm applied with the optimal smoothing factor improved the COV and CNR by 66.94% and 8.00% on average, respectively, compared to those of the original image. In conclusion, an optimized smoothing factor was derived from the NLM approach-based algorithm in brain SPECT images and may be applicable to various nuclear medicine imaging techniques in the future.

Keywords

Acknowledgement

This work was supported by the Gachon University research fund of 2022 (GCU-202206110001) and was supported by the National Research Foundation of Korea (NRF-2021R1F1A1061440). We would like to thank Yongho Do who works at Seoul Metropolitan Government Seoul National University Boramae Medical Center for helping us acquire SPECT data.

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