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Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 494691, 9 pages
http://dx.doi.org/10.1155/2015/494691
Research Article

Adaptive Autoregressive Model for Reduction of Noise in SPECT

1Division of Nuclear Medicine, Department of Diagnostic Radiology, Oulu University Hospital (OYS), P.O. Box 500, 90029 Oulu, Finland
2Department of Automation Science and Engineering, Tampere University of Technology, P.O. Box 692, 33101 Tampere, Finland
3Joint Authority for Päijät-Häme Social and Health Care, Department of Clinical Physiology and Nuclear Medicine, Keskussairaalankatu 7, 15850 Lahti, Finland

Received 2 September 2014; Revised 5 November 2014; Accepted 2 December 2014

Academic Editor: Liang Li

Copyright © 2015 Reijo Takalo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. M. Lyra and A. Ploussi, “Filtering in SPECT image reconstruction,” International Journal of Biomedical Imaging, vol. 2011, Article ID 693795, 14 pages, 2011. View at Publisher · View at Google Scholar · View at Scopus
  2. P. Zanzonico, “Technical requirements for SPECT: instrumentation, data acquisition and processing, and quality control,” in Clinical SPECT Imaging, E. L. Kramer and J. J. Sanger, Eds., pp. 7–41, Raven Press, New York, NY, USA, 1995. View at Google Scholar
  3. T. S. Kangasmaa, J. T. Kuikka, E. J. Vanninen, H. M. Mussalo, T. P. Laitinen, and A. O. Sohlberg, “Half-time myocardial perfusion SPECT imaging with attenuation and Monte Carlo-based scatter correction,” Nuclear Medicine Communications, vol. 32, no. 11, pp. 1040–1045, 2011. View at Publisher · View at Google Scholar · View at Scopus
  4. R. Takalo, H. Hytti, and H. Ihalainen, “Adaptive autoregressive model for reduction of poisson noise in scintigraphic images,” Journal of Nuclear Medicine Technology, vol. 39, no. 1, pp. 19–26, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. J. Biemond, R. L. Lagendijk, and R. M. Mersereau, “Iterative methods for image deblurring,” Proceedings of the IEEE, vol. 78, no. 5, pp. 856–883, 1990. View at Publisher · View at Google Scholar · View at Scopus
  6. H. Onishi, N. Motomura, M. Takahashi, M. Yanagisawa, and K. Ogawa, “A 3-dimensional mathematic cylinder phantom for the evaluation of the fundamental performance of SPECT,” Journal of Nuclear Medicine Technology, vol. 38, no. 1, pp. 42–48, 2010. View at Publisher · View at Google Scholar · View at Scopus
  7. L. Li, W. Hou, X. Zhang, and M. Ding, “GPU-based block-wise nonlocal means denoising for 3D ultrasound images,” Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 921303, 10 pages, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. I. G. Zubal, C. R. Harrell, E. O. Smith, Z. Rattner, G. Gindi, and P. B. Hoffer, “Computerized three-dimensional segmented human anatomy,” Medical Physics, vol. 21, no. 2, pp. 299–302, 1994. View at Publisher · View at Google Scholar · View at Scopus
  9. R. A. Brooks and D. G. Chiro, “Principles of computer assisted tomography (CAT) in radiographic and radioisotopic imaging,” Physics in Medicine and Biology, vol. 21, no. 5, pp. 689–732, 1976. View at Google Scholar · View at Scopus
  10. H. M. Hudson and R. S. Larkin, “Accelerated image reconstruction using ordered subsets of projection data,” IEEE Transactions on Medical Imaging, vol. 13, no. 4, pp. 601–609, 1994. View at Publisher · View at Google Scholar · View at Scopus
  11. S. Butterworth, “On the theory of filter amplifiers,” Wireless Engineering, vol. 7, pp. 536–541, 1930. View at Google Scholar
  12. W. A. Edelstein, P. A. Bottomley, H. R. Hart, and L. S. Smith, “Signal, noise, and contrast in nuclear magnetic resonance (NMR) imaging,” Journal of Computer Assisted Tomography, vol. 7, no. 3, pp. 391–401, 1983. View at Publisher · View at Google Scholar · View at Scopus
  13. S. D. Wollenweber and K. L. Gould, “Investigation of cold contrast recovery as a function of acquisition and reconstruction parameters for 2D cardiac PET,” in Proceedings of the IEEE Nuclear Science Symposium Conference Record (NSS/MIC '05), vol. 5, pp. 2552–2556, October 2005. View at Publisher · View at Google Scholar · View at Scopus
  14. G. Gindi, M. Lee, A. Rangarajan, and I. G. Zubal, “Bayesian reconstruction of functional images using anatomical information as priors,” IEEE Transactions on Medical Imaging, vol. 12, no. 4, pp. 670–680, 1993. View at Publisher · View at Google Scholar · View at Scopus
  15. R. C. Gonzales and R. E. Woods, Digital Image Processing, Prentice Hall, Upper Saddle River, NJ, USA, 2002.