Application of wavelet domain Wiener filtering algorithm to cone-beam dental CT

Zhang Chengxin; Chen Yunbin; Li Shoutao; Liu Qinghua; Wang Yuan; Chen Hao

Volume 25 Issue S0

Jun. 2013

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Abstract

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Article Navigation > High Power Laser and Particle Beams > 2013 > 25(S0): 33-38

jiao chunye, wang feng, liu shenye, et al. Full aperture backscatter signal analysis of laser with hohlraum on Shenguang Ⅱ laser facility[J]. High Power Laser and Particle Beams, 2010, 22.

Citation:

Zhang Chengxin, Chen Yunbin, Li Shoutao, et al. Application of wavelet domain Wiener filtering algorithm to cone-beam dental CT[J]. High Power Laser and Particle Beams, 2013, 25: 33-38.

jiao chunye, wang feng, liu shenye, et al. Full aperture backscatter signal analysis of laser with hohlraum on Shenguang Ⅱ laser facility[J]. High Power Laser and Particle Beams, 2010, 22.

Citation:

Zhang Chengxin, Chen Yunbin, Li Shoutao, et al. Application of wavelet domain Wiener filtering algorithm to cone-beam dental CT[J]. High Power Laser and Particle Beams, 2013, 25: 33-38.

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Application of wavelet domain Wiener filtering algorithm to cone-beam dental CT

Zhang Chengxin^{1,2,3
,
,},
Chen Yunbin^1,2,
Li Shoutao^1,2,
Liu Qinghua^1,2,
Wang Yuan^1,2,
Chen Hao^1,2

1.
Institute of Applied Electronics,CAEP,Mianyang 621900,China;
2.
National X-ray Digital Imaging Instrument Center,Mianyang 621900,China;
3.
Institute of Physics Electronics,University of Electronic Science and Technology of China,Chengdu 610054,China

Received Date: 2013-01-30
Rev Recd Date: 2013-03-20
Publish Date: 2013-05-15

Abstract

Abstract

A wavelet domain Wiener filtering method is proposed for denoising of cone-beam dental CT images. The db4 wavelet is used to decompose the CT image, and the Wiener filtering is implemented in each scale of wavelet coefficients, while the parameters of local mean and noise variance estimation are adjusted based on region statistical characteristics in each scale of wavelet coefficients. New wavelet coefficients are used for the reconstruction of the denoised image, and the denoised CT image is obtained. The results of computer simulation and the cone-beam dental CT actual data prove that this method raises the reconstruction images signal-to-noise ratio, suppresses image noise effectively, and then improves the image visual effect obviously.
- wavelet transform,
- Wiener filter,
- cone beam dental CT,
- image denoising,
- estimation of noise variance

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