ON SOME ERRORS AND BIAS IN PROTON COMPUTED TOMOGRAPHY

2011 ◽  
Vol 26 (10n11) ◽  
pp. 1761-1774 ◽  
Author(s):  
BELA ERDELYI

Novel accelerator technology, including Fixed Field Alternating Gradient Accelerators (FFAG) coupled with medical imaging devices, hold significant promise for enhanced proton therapy. The accuracy and efficiency of proton therapy treatments will see improvements with the implementation of proton computed tomography (pCT), currently under development. Here, we analyze the robustness of the image reconstruction method in pCT with respect to three different error sources and conclude that pCT is inherently resilient with respect to errors in mean ionization potential, discrete sampling of proton trajectories and bias in the limit of large radiation doses.

2021 ◽  
pp. 1-24
Author(s):  
Changcheng Gong ◽  
Li Zeng

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.


2018 ◽  
Vol 34 (6) ◽  
pp. 064001 ◽  
Author(s):  
Daniil Kazantsev ◽  
Jakob S Jørgensen ◽  
Martin S Andersen ◽  
William R B Lionheart ◽  
Peter D Lee ◽  
...  

2011 ◽  
Vol 19 (2) ◽  
pp. 229-247 ◽  
Author(s):  
Marius Costin ◽  
Delphine Lazaro-Ponthus ◽  
Samuel Legoupil ◽  
Philippe Duvauchelle ◽  
Valérie Kaftandjian

Sign in / Sign up

Export Citation Format

Share Document