Nonlinear Anisotropic Filtering with Considering of Various Structures in Magnetic Resonance Imaging

자기공명영상에서 다양한 구조들을 고려한 비선형 이방성 필터링

  • 송영철 (경북대 전자전기공학부)
  • Published : 2003.03.01

Abstract

In this paper, a nonlinear anisotropic filtering method without the loss of important information happened due to the repeated filtering in magnetic resonance images is proposed. First of all original images are divided into four regions, e.g., SPR(Strong Plain Region), EPR(Easy Plain Region), SER(Strong Edge Region), and EER(Easy Edge Region). An optimal template among multiple templates is selected, then the nonlinear anisotropic filtering based on the template is applied in pixel by pixel basis. In the proposed algorithm, filtering strength of EER containing important information is adjusted very weak and filtering strength for remaining regions is also adjusted according to the degree of the importance. In spite of repeated filtering, resulting images by the proposed method could still preserve anatomy information of original images without any degradation. Compared to the existing nonlinear anisotropic filtering, the proposed filtering method with multiple templates provides higher reliability for filtered images.

Keywords

References

  1. R.C. Gonzalez and R.E. Woods, Digital Image Processding, Addison-Wesley, pp. 191-195, 1992
  2. P. Chan and J.S. Lim, 'One-Dimensional processing for adaptive image restoration,' IEEE Trans. ASSP, vol. 33, pp. 117-126, February 1985 https://doi.org/10.1109/TASSP.1985.1164534
  3. K. Rank and . Unbehauen, 'An adaptive recursive 2-D filter for removal of gaussian noise in images,' IEEE Trans. Imag. Proc. vol. 1, pp. 431-436, July 1992 https://doi.org/10.1109/83.148617
  4. G. Gerig, O. Kubler, R. Kikinis, and A. Jolesz, 'Nonlinear anisotropic filtering of MRI data,' IEEE Trans. Med. Imag. vol.11, pp.221-232, 1992 https://doi.org/10.1109/42.141646
  5. C. B. Ahn, Y. C. Song, and D. J. Park, 'Adaptive template filtering for signal-to-noise ratio enhancement in magnetic resonance imaging,' IEEE Trans. Med. Imag., vol. 18, no. 6, pp. 549-556, June 1999 https://doi.org/10.1109/42.781019
  6. P. Perona and J. Malik, 'Scale-space and edge detection using anisotropic diffusion,' IEEE Trans. Pattern Anal. Machine Intell., vol. 12, no. 7, pp. 629-639, July 1990 https://doi.org/10.1109/34.56205
  7. A. Papoulis, Probability, Random Variables, and Stochastic Processes, McGraw-Hill, Tokyo, 1965
  8. A. Macovski, Noise in MRI, Magn. Reson. Med., vol. 36, pp. 494-497, April 1996 https://doi.org/10.1002/mrm.1910360327