Paper
11 September 2013 Study on an improved filtered back-projection image reconstruction algorithm combined with wavelet denoising
Zhong Ren, Guodong Liu, Zhen Huang
Author Affiliations +
Proceedings Volume 8907, International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications; 890710 (2013) https://doi.org/10.1117/12.2031888
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China
Abstract
In the process of medical imaging (MI) reconstruction, filtering of original projection data is a key step to overcome artifact of the reconstructed image. Although some classical filters can be used into FBP algorithm, some drawbacks limit its application in practice, especially for the data polluted by non-stationary random noises. To overcome the shortcomings of these traditional filtering, an improved FBP combined with a shift-invariant wavelet threshold denoising algorithm is proposed in this paper. In the experiments, the reconstructed effects were compared between the improved algorithm, classical soft and hard threshold denoising methods. Experimental results illustrated that the reconstruction effect of improved FBP algorithm is better than that of others. In addition, two evaluation standards, i.e. mean-square error (MSE), peak-to-peak signal-noise ratio (PSNR) were used to compare the results of different algorithms. It was found that the reconstructed effects of the improved FBP combined with shift-invariant wavelet hard threshold function based on RL filter is better than others. Therefore, this improved FBP algorithm has potential value in the medical imaging.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhong Ren, Guodong Liu, and Zhen Huang "Study on an improved filtered back-projection image reconstruction algorithm combined with wavelet denoising", Proc. SPIE 8907, International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications, 890710 (11 September 2013); https://doi.org/10.1117/12.2031888
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KEYWORDS
Wavelets

Reconstruction algorithms

Denoising

Image filtering

Image restoration

Medical imaging

Stereolithography

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