scholarly journals Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging

2012 ◽  
Vol 39 (6Part1) ◽  
pp. 3343-3360 ◽  
Author(s):  
Mehrsima Abdoli ◽  
Rudi A. J. O. Dierckx ◽  
Habib Zaidi
Keyword(s):  
Attenuation Correction ◽  
Ct Imaging ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Pet Ct ◽  
Reduction Strategies

Impact of different iterative metal artifact reduction (iMAR) algorithms on PET/CT attenuation correction after port implementation

2020 ◽  
Vol 129 ◽  
pp. 109065
Author(s):  
Ole Martin ◽  
Johannes Boos ◽  
Joel Aissa ◽  
Christian Vay ◽  
Philipp Heusch ◽  
...  
Keyword(s):  
Attenuation Correction ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Pet Ct ◽  
Ct Attenuation

scholarly journals Impact of different metal artifact reduction techniques on attenuation correction in 18F-FDG PET/CT examinations

2020 ◽  
Vol 93 (1105) ◽  
pp. 20190069 ◽  
Author(s):  
Ole Martin ◽  
Joel Aissa ◽  
Johannes Boos ◽  
Katrin Wingendorf ◽  
David Latz ◽  
...  
Keyword(s):  
Attenuation Correction ◽  
Dark Band ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Metal Implants ◽  
Pet Quantification ◽  
Oncological Patients ◽  
Pet Ct ◽  
The Impact

Objective: To evaluate the impact of different metal artifact reduction (MAR) algorithms on Hounsfield unit (HU) and standardized uptake values (SUV) in a phantom setting and verify these results in patients with metallic implants undergoing oncological PET/CT examinations. Methods and materials: In this prospective study, PET-CT examinations of 28 oncological patients (14 female, 14 male, mean age 69.5 ± 15.2y) with 38 different metal implants were included. CT datasets were reconstructed using standard weighted filtered back projection (WFBP) without MAR, MAR in image space (MARIS) and iterative MAR (iMAR, hip algorithm). The three datasets were used for PET attenuation correction. SUV and HU measurements were performed at the site of the most prominent bright and dark band artifacts. Differences between HU and SUV values across the different reconstructions were compared using paired t-tests. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.017). Results: For bright band artifacts, MARIS led to a non-significant mean decrease of 12.0% (345 ± 315 HU) in comparison with WFBP (391 ± 293 HU), whereas iMAR led to a significant decrease of 68.3% (125 ± 185 HU, p < 0.017). For SUVmean, MARIS showed no significant effect in comparison with WFBP (WFBP: 0.99 ± 0.40, MARIS: 0.96 ± 0.39), while iMAR led to a significant decrease of 11.1% (0.88 ± 0.35, p < 0.017). Similar results were observed for dark band artifacts. Conclusion: iMAR significantly reduces artifacts caused by metal implants in CT and thus leads to a significant change of SUV measurements in bright and dark band artifacts compared with WFBP and MARIS, thus probably improving PET quantification. Advances in knowledge: The present work indicates that MAR algorithms such as iMAR algorithm in integrated PET/CT scanners are useful to improve CT image quality as well as PET quantification in the evaluation of tracer uptake adjacent to large metal implants. A detailed analysis of oncological patients with various large metal implants using different MAR algorithms in PET/CT has not been conducted yet.

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.

Impact of iterative metal artifact reduction on diagnostic image quality in patients with dental hardware

2016 ◽  
Vol 58 (3) ◽  
pp. 279-285 ◽  
Author(s):  
Jakob Weiß ◽  
Christoph Schabel ◽  
Malte Bongers ◽  
Rainer Raupach ◽  
Stephan Clasen ◽  
...  
Keyword(s):  
Image Quality ◽  
Ct Imaging ◽  
Diagnostic Image Quality ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Metal Artifacts ◽  
Diagnostic Image ◽  
Anatomical Structures ◽  
Dental Fillings

Background Metal artifacts often impair diagnostic accuracy in computed tomography (CT) imaging. Therefore, effective and workflow implemented metal artifact reduction algorithms are crucial to gain higher diagnostic image quality in patients with metallic hardware. Purpose To assess the clinical performance of a novel iterative metal artifact reduction (iMAR) algorithm for CT in patients with dental fillings. Material and Methods Thirty consecutive patients scheduled for CT imaging and dental fillings were included in the analysis. All patients underwent CT imaging using a second generation dual-source CT scanner (120 kV single-energy; 100/Sn140 kV in dual-energy, 219 mAs, gantry rotation time 0.28–1/s, collimation 0.6 mm) as part of their clinical work-up. Post-processing included standard kernel (B49) and an iterative MAR algorithm. Image quality and diagnostic value were assessed qualitatively (Likert scale) and quantitatively (HU ± SD) by two reviewers independently. Results All 30 patients were included in the analysis, with equal reconstruction times for iMAR and standard reconstruction (17 s ± 0.5 vs. 19 s ± 0.5; P > 0.05). Visual image quality was significantly higher for iMAR as compared with standard reconstruction (3.8 ± 0.5 vs. 2.6 ± 0.5; P < 0.0001, respectively) and showed improved evaluation of adjacent anatomical structures. Similarly, HU-based measurements of degree of artifacts were significantly lower in the iMAR reconstructions as compared with the standard reconstruction (0.9 ± 1.6 vs. –20 ± 47; P < 0.05, respectively). Conclusion The tested iterative, raw-data based reconstruction MAR algorithm allows for a significant reduction of metal artifacts and improved evaluation of adjacent anatomical structures in the head and neck area in patients with dental hardware.

Sign in / Sign up

Export Citation Format

Share Document