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Proceedings Paper

Improvement of wavelet threshold filtered back-projection image reconstruction algorithm
Author(s): Zhong Ren; Guodong Liu; Zhen Huang
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Paper Abstract

Image reconstruction technique has been applied into many fields including some medical imaging, such as X ray computer tomography (X-CT), positron emission tomography (PET) and nuclear magnetic resonance imaging (MRI) etc, but the reconstructed effects are still not satisfied because original projection data are inevitably polluted by noises in process of image reconstruction. Although some traditional filters e.g., Shepp-Logan (SL) and Ram-Lak (RL) filter have the ability to filter some noises, Gibbs oscillation phenomenon are generated and artifacts leaded by back-projection are not greatly improved. Wavelet threshold denoising can overcome the noises interference to image reconstruction. Since some inherent defects exist in the traditional soft and hard threshold functions, an improved wavelet threshold function combined with filtered back-projection (FBP) algorithm was proposed in this paper. Four different reconstruction algorithms were compared in simulated experiments. Experimental results demonstrated that this improved algorithm greatly eliminated the shortcomings of un-continuity and large distortion of traditional threshold functions and the Gibbs oscillation. Finally, the availability of this improved algorithm was verified from the comparison of two evaluation criterions, i.e. mean square error (MSE), peak signal to noise ratio (PSNR) among four different algorithms, and the optimum dual threshold values of improved wavelet threshold function was gotten.

Paper Details

Date Published: 24 November 2014
PDF: 10 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010G (24 November 2014); doi: 10.1117/12.2069632
Show Author Affiliations
Zhong Ren, Jiangxi Science and Technology Normal Univ. (China)
Nanchang Univ. (China)
Guodong Liu, Jiangxi Science and Technology Normal Univ. (China)
Zhen Huang, Jiangxi Science and Technology Normal Univ. (China)


Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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