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Noise-weighted spatial domain FBP algorithm
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DOI：10.1118/1.4870989.png)
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摘要
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Purpose: The purpose of this paper is to implement a noise-weighted filtered backprojection (FBP) algorithm in the form of convolution backprojection, but this convolution has a spatially variant integration kernel. Methods: Noise-weighted FBP algorithms have been developed in recent years, with filtering being performed in the Fourier domain. The noise weighting makes the ramp filter in the FBP algorithm shift-varying. It is not efficient to implement shift-varying filtration in the Fourier domain. It is known that Fourier-domain multiplication is equivalent to spatial-domain convolution. An expansion method is suggested in this paper to obtain a closed-form integration kernel. Results: The noise weighted FBP algorithm can now be implemented in the spatial domain efficiently. The total computation cost is less than that of the Fourier domain implementation. Conclusions: Computer simulations are used to show the three-term expansion method to approximate the filter kernel. A clinical study is used to verify the feasibility of the proposed algorithm. (C) 2014 American Association of Physicists in Medicine.
Keyword:
image reconstruction
analytical reconstruction algorithm
tomography
noise modeling
CT
convolution
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IF:
3.2
论文数:
3.7W
被引数:
3.2W
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