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| 3-D Total Generalized Variation Method for Dynamic Cardiac MR Image Denoising |
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Abstract Total Generalized Variation (TGV) regularization model is one of the
most effective methods for MR image denoising. However, for 3D
dynamic MR image, the TGV regularization model cannot use the
correlated information of each slice. Therefore, in order to
effectively denoising the dynamic MR image, 3D Total Generalized
total Variation (3D-TGV) is proposed to denoise different kinds
noise in the dynamic MR image. Experimental results show that,
compared with the Total Variation (TV) and Total Generalized
Variation (TGV), the proposed 3D TGV method has a better
performance, and can significantly improve the denoising effect,
with higher Signal-to-noise Ratio (SNR) and fewer artifacts.
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| Cite this article: |
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Mingfeng Jiang,Lulu Han,Yaming Wang, et al. 3-D Total Generalized Variation Method for Dynamic Cardiac MR Image Denoising[J]. Journal of Fiber Bioengineering and Informatics, 2015, 8(3): 557-564.
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2015, Vol. 8 
