A field of view based metal artifact reduction method with the presence of data truncation

2019 ◽  
Author(s):  
Seungwon Choi ◽  
Seunghyuk Moon ◽  
Jongduk Baek
Keyword(s):  
Reduction Method ◽  
Field Of View ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Data Truncation

scholarly journals A metal artifact reduction method for small field of view CT imaging

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0227656
Author(s):  
Seungwon Choi ◽  
Seunghyuk Moon ◽  
Jongduk Baek
Keyword(s):  
General Assumption ◽  
Ct Imaging ◽  
Previous Method ◽  
Field Of View ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Missing Information ◽  
Data Truncation ◽  
Small Field Of View

Several sinogram inpainting based metal artifact reduction (MAR) methods have been proposed to reduce metal artifact in CT imaging. The sinogram inpainting method treats metal trace regions as missing data and estimates the missing information. However, a general assumption with these methods is that data truncation does not occur and that all metal objects still reside within the field-of-view (FOV). These assumptions are usually violated when the FOV is smaller than the object. Thus, existing inpainting based MAR methods are not effective. In this paper, we propose a new MAR method to effectively reduce metal artifact in the presence of data truncation. The main principle of the proposed method involves using a newly synthesized sinogram instead of the originally measured sinogram. The initial reconstruction step involves obtaining a small FOV image with the truncation artifact removed. The final step is to conduct sinogram inpainting based MAR methods, i.e., linear and normalized MAR methods, on the synthesized sinogram from the previous step. The proposed method was verified for extended cardiac-torso simulations, clinical data, and experimental data, and its performance was quantitatively compared with those of previous methods (i.e., linear and normalized MAR methods directly applied to the originally measured sinogram data). The effectiveness of the proposed method was further demonstrated by reducing the residual metal artifact that were present in the reconstructed images obtained using the previous method.

scholarly journals A metal artifact reduction method for small field of view CT imaging

2019 ◽  
Author(s):  
Seungwon Choi ◽  
Seunghyuk Moon ◽  
Jongduk Baek
Keyword(s):  
Mean Squared Error ◽  
Main Idea ◽  
Previous Method ◽  
Field Of View ◽  
Projection Data ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Metal Artifacts ◽  
Data Truncation

AbstractTo reduce metal artifacts, several sinogram inpainting-based metal artifact reduction (MAR) methods have been proposed where projection data within the metal trace region of the sinogram are treated as missing and subsequently estimated. However, these methods generally assume data truncation does not occur and all metal objects reside inside the field-of-view (FOV). For small FOV imaging, these assumptions are violated, and thus existing inpainting-based MAR methods would not be effective. In this paper, we propose a new MAR method to reduce metal artifacts effectively in the presence of data truncation. The main idea behind the proposed method is the synthesis of a sinogram, which is treated as the originally measured sinogram. First, an initial reconstruction step is performed to remove truncation artifacts. The next step consists of a forward projection of the small FOV image, replacing the original sinogram with the synthesized sinogram. The final step is the application of sinogram inpainting based MAR methods using the synthesized sinogram. Verification of the proposed method was performed for three situations: extended cardiac-torso (XCAT) simulation, clinical data, and experimental data. The proposed method was applied with linear MAR (LMAR) and normalized MAR (NMAR), and the performance of the proposed method was compared with that of the previous method. For quantitative evaluation, normalized mean squared error (NMSE) and structure similarity (SSIM) were used. The results show the effectiveness of the proposed method to reduce residual metal artifacts, which are present in the results obtained with the previous method. The evaluation results using NMSE and SSIM also indicate that the proposed method is more effective than the previous method.

scholarly journals Metal Artifact Reduction Method Based on Noncoplanar Scanning in CBCT Imaging

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 7236-7243
Author(s):  
Gao Liugang ◽  
Sui Jianfeng ◽  
Lin Tao ◽  
Xie Kai ◽  
Ni Xinye
Keyword(s):  
Reduction Method ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction

scholarly journals An additional tilted-scan-based CT metal-artifact-reduction method for radiation therapy planning

2018 ◽  
Vol 20 (1) ◽  
pp. 237-249 ◽  
Author(s):  
Changhwan Kim ◽  
Rizza Pua ◽  
Chung-Hwan Lee ◽  
Da-in Choi ◽  
Byungchul Cho ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Reduction Method ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Therapy Planning ◽  
Radiation Therapy Planning
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