Dual-energy CT Reconstruction using Guided Image Filtering

Author(s):  
Hongkai Yang ◽  
Kyungsang Kim ◽  
Georges El Fakhri ◽  
Kejun Kang ◽  
Yuxiang Xing ◽  
...  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Tianyi Wang ◽  
Chengxiang Wang ◽  
Kequan Zhao ◽  
Wei Yu ◽  
Min Huang

Abstract Limited-angle computed tomography (CT) reconstruction problem arises in some practical applications due to restrictions in the scanning environment or CT imaging device. Some artifacts will be presented in image reconstructed by conventional analytical algorithms. Although some regularization strategies have been proposed to suppress the artifacts, such as total variation (TV) minimization, there is still distortion in some edge portions of image. Guided image filtering (GIF) has the advantage of smoothing the image as well as preserving the edge. To further improve the image quality and protect the edge of image, we propose a coupling method, that combines ℓ 0 {\ell_{0}} gradient minimization and GIF. An intermediate result obtained by ℓ 0 {\ell_{0}} gradient minimization is regarded as a guidance image of GIF, then GIF is used to filter the result reconstructed by simultaneous algebraic reconstruction technique (SART) with nonnegative constraint. It should be stressed that the guidance image is dynamically updated as the iteration process, which can transfer the edge to the filtered image. Some simulation and real data experiments are used to evaluate the proposed method. Experimental results show that our method owns some advantages in suppressing the artifacts of limited angle CT and in preserving the edge of image.


2020 ◽  
Vol 58 (11) ◽  
pp. 2621-2629
Author(s):  
Yuanwei He ◽  
Li Zeng ◽  
Wei Yu ◽  
Changcheng Gong

2011 ◽  
Author(s):  
M. Depypere ◽  
J. Nuyts ◽  
N. van Gastel ◽  
G. Carmeliet ◽  
F. Maes ◽  
...  

2018 ◽  
Vol 109 ◽  
pp. 218-222
Author(s):  
Sven S. Walter ◽  
Sven Schneeweiß ◽  
Michael Maurer ◽  
Mareen S. Kraus ◽  
Julian L. Wichmann ◽  
...  

2018 ◽  
Vol 45 (5) ◽  
pp. 2129-2142 ◽  
Author(s):  
Shuangyue Zhang ◽  
Dong Han ◽  
David G. Politte ◽  
Jeffrey F. Williamson ◽  
Joseph A. O'Sullivan

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 99954-99963 ◽  
Author(s):  
Jiaxi Wang ◽  
Chengxiang Wang ◽  
Yumeng Guo ◽  
Wei Yu ◽  
Li Zeng

Author(s):  
Yuanyuan Liu ◽  
Peng Zheng ◽  
Chunming Zhang

Dual energy CT (DECT) has become a hot topic for its high detection precision and robust material identification ability in the field of nuclear safety and security inspection. However, the high cost of the system becomes a big limitation for its wide usage. To solve this problem, in 2009, we have proposed a dual energy CT reconstruction method with reduced data (DECT-RD) requiring much fewer data to reduce the cost of detectors. However, it is a simple idea without more analyzing in the process of solving ill-posed equations. In this paper, we tried to solve ill-posed equations with constraint condition (DECT-RDCC) and least squares (DECT-RDLS) respectively. Numerical simulations are done by using DECT-RD, DECT-RDCC and DECT-RDLS in the same situation, only 7 dual energy detector bins instead of 256 complete bin sampling in each projection. Results demonstrated that DECT-RDCC with relative error less than 1.1% is better than DECT-RD with relative error less than 1.8% while DECT-RDLS plays a more exact and steady role with relative error less than 0.6% than DECT-RDCC. Hence, DECT-RDLS is a better method used to obtain much lower system cost. We believe this work will drive DECT into wide usage.


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