Curvature constraint based image reconstruction for limited-angle computed tomography

2019 ◽  
Author(s):  
Xiao Xue ◽  
Shusen Zhao ◽  
Yunsong Zhao ◽  
Peng Zhang
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Curvature Constraint ◽  
Limited Angle

Image reconstruction for limited-angle computed tomography with curvature constraint

2019 ◽  
Vol 30 (12) ◽  
pp. 125401
Author(s):  
Xiao Xue ◽  
Shusen Zhao ◽  
Yunsong Zhao ◽  
Peng Zhang
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Curvature Constraint ◽  
Limited Angle

Anisotropic structure property based image reconstruction method for limited-angle computed tomography

2021 ◽  
pp. 1-24
Author(s):  
Changcheng Gong ◽  
Li Zeng
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Projection Data ◽  
Reconstruction Technique ◽  
Reconstruction Method ◽  
Anisotropic Structure ◽  
Structure Property ◽  
Image Reconstruction Method ◽  
Ct Data ◽  
Limited Angle

Limited-angle computed tomography (CT) may appear in restricted CT scans. Since the available projection data is incomplete, the images reconstructed by filtered back-projection (FBP) or algebraic reconstruction technique (ART) often encounter shading artifacts. However, using the anisotropy property of the shading artifacts that coincide with the characteristic of limited-angle CT images can reduce the shading artifacts. Considering this concept, we combine the anisotropy property of the shading artifacts with the anisotropic structure property of an image to develop a new algorithm for image reconstruction. Specifically, we propose an image reconstruction method based on adaptive weighted anisotropic total variation (AwATV). This method, termed as AwATV method for short, is designed to preserve image structures and then remove the shading artifacts. It characterizes both of above properties. The anisotropy property of the shading artifacts accounts for reducing artifacts, and the anisotropic structure property of an image accounts for preserving structures. In order to evaluate the performance of AwATV, we use the simulation projection data of FORBILD head phantom and real CT data for image reconstruction. Experimental results show that AwATV can always reconstruct images with higher SSIM and PSNR, and smaller RMSE, which means that AwATV enables to reconstruct images with higher quality in term of artifact reduction and structure preservation.

Iterative image reconstruction using modified non-local means filtering for limited-angle computed tomography

2016 ◽  
Vol 32 (9) ◽  
pp. 1041-1051 ◽  
Author(s):  
Hongliang Qi ◽  
Zijia Chen ◽  
Shuyu Wu ◽  
Yuan Xu ◽  
Linghong Zhou
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Iterative Image Reconstruction ◽  
Local Means ◽  
Non Local ◽  
Limited Angle
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