Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Median modified wiener filter for improving the image quality of gamma camera images

  • Park, Chan Rok (Department of Nuclear Medicine, Seoul National University Hospital) ;
  • Kang, Seong-Hyeon (Department of Radiological Science, Gachon University) ;
  • Lee, Youngjin (Department of Radiological Science, Gachon University)
  • Received : 2019.12.13
  • Accepted : 2020.03.21
  • Published : 2020.10.25
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Abstract

The filter technique was applied to noise images, as noise is the significant factor that cause poor image quality due to lower photon counting. The purpose of this study is to confirm that image quality can be improved using the median modified Wiener filter (MMWF) technique; this is achieved via a National Electrical Manufacturers Association International Electrotechnical Commission body phantom with four large spheres that are filled with the 99mTc radioisotope when evaluating the image quality. Conventional filters such as Wiener, Gaussian, and median filters were designed, and signal to noise ratio, coefficient of variation, and contrast to noise ratio were used as the evaluation parameters. The improvement in the image quality was in the following order, from the least to the highest improvement, in all cases: Wiener filter, Gaussian filter, median filter, and the MMWF technique. The results show that the image quality was improved from 20.6 to 65.5%, 7.4-40.3%, and 12.7-44.7% for the SNR, COV, and CNR values, respectively, when using the MMWF technique, compared with the use of conventional filters. In conclusion, our results demonstrated that the MMWF technique is useful for reducing the noise distribution in gamma camera images.

Keywords

References

  1. R.J. Jaszczak, R.E. Goleman, C.B. Lim, SPECT: single photon emission computed tomography, IEEE Trans. Nucl. Sci. NS- 27 (1980) 1137-1153. https://doi.org/10.1109/TNS.1980.4330986
  2. R.J. Jaszczak, L.T. Chang, P.H. Murphy, Single photon emission computed tomography using multi-slice fan beam collimators, IEEE Trans. Nucl. Sci. NS-26 (1979) 610-618. https://doi.org/10.1109/TNS.1979.4329698
  3. R.J. Jaszczak, L.T. Chang, N.A. Stein, F.E. Moore, Whole-body single-photon emission computed tomography using dual, large-field-of-view tomography scintillation cameras, Phys. Med. Biol. 24 (1979) 1123-1143. https://doi.org/10.1088/0031-9155/24/6/003
  4. M.T. Madsen, Recent advances in SPECT imaging, J. Nucl. Med. 48 (2007) 661-673. https://doi.org/10.2967/jnumed.106.032680
  5. B.M.W. Tsui, The AAPM/RSNA physics tutorials for resident, Radiographics 16 (1996) 173-183. https://doi.org/10.1148/radiographics.16.1.173
  6. M.N. Do, M. Vetterli, The contourlet transform: an efficient directional multiresolution image representation, IEEE Trans. Image Process. 14 (2005) 2091-2106.
  7. R.D. Appel, J.R. Vargas, P.M. Palagi, D. Walther, D.F. Hochstrasser, Melanie II - a third-generation software package for analysis of two-dimensional electrophoresis images: II. Algorithms, Electrophoresis 18 (1997) 2735-2748. https://doi.org/10.1002/elps.1150181507
  8. P. Tsakanikas, I. Manolakos, Effective denoising of 2D gel proteomics images using contourlets, IEEE Int. Conf. Image Process. 2 (2007) 1-22.
  9. C.V. Cannistraci, F.M. Montevecchi, M. Alessio, Median-modified Wiener filter provides efficient denoising, preserving spot edge and morphology in 2-DE image processing, Proteomics 9 (2009) 4908-4919. https://doi.org/10.1002/pmic.200800538
  10. H. Hwang, R.A. Hadded, Adaptive median filter: new algorithms and results, IEEE Trans. Image Process. 4 (1995) 499-502. https://doi.org/10.1109/83.370679
  11. G. Deng, L. Cahill, An adaptive Gaussian filter for noise reduction and edge detection, IEEE Nucl. Sci. Med. Image (1993) 1615-1619.
  12. M.P. Ekstrom, Realizable Wiener filtering in two dimensions, IEEE Trans. Acoust., Speech, Signal Proc., ASSP 30 (1982) 31-40. https://doi.org/10.1109/TASSP.1982.1163844
  13. A. Sharma, J. Singh, Image denoising using spatial domain filters: a quantitative study, in: 6th International Congress on Image and Signal Processing, CISP, 2013, pp. 293-298.
  14. S. Esakkirajan, T. Veerakumar, A.N. Subramanyam, C.H. PremChand, Removal of high density Salt and pepper noise through modified decision based Unsymmetrical trimmed median filter, IEEE Signal Process. Lett. 18 (2011) 287-290. https://doi.org/10.1109/LSP.2011.2122333
  15. C.V. Cannistraci, A. Abbas, X. Gao, Median modified wiener filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra, Sci. Rep. 5 (2015) 8017, https://doi.org/10.1038/srep08017.

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