Evaluation of the quality of CT images acquired with smart metal artifact reduction software
Objective: To evaluate the practical effectiveness of smart metal artifact reduction (SMAR) in reducing artifacts caused by metallic implants. Methods: Patients with metal implants underwent computed tomography (CT) examinations on high definition CT scanner, and the data were reconstructed with adaptive statistical iterative reconstruction (ASiR) with value weighted to 40% and smart metal artifact reduction (SMAR) technology. The comparison was assessed by both subjective and objective assessment between the two groups of images. In terms of subjective assessment, three radiologists evaluated image quality and assigned a score for visualization of anatomic structures in the critical areas of interest. Objectively, the absolute CT value of the difference (ΔCT) and artifacts index (AI) were adopted in this study for the quantitative assessment of metal artifacts. Results: In subjective image quality assessment, three radiologists scored SMAR images higher than 40% ASiR images (P<0.01) and the result suggested that visualization of critical anatomic structures around the region of the metal object was significantly improved by using SMAR compared with 40% ASiR. The ΔCT and AI for quantitative assessment of metal artifacts showed that SMAR appeared to be superior for reducing metal artifacts (P<0.05) and indicated that this technical approach was more effective in improving the quality of CT images. Conclusion: A variety of hardware (dental filling, embolization coil, instrumented spine, hip implant, knee implant) are processed with the SMAR algorithm to demonstrate good recovery of soft tissue around the metal. This artifact reduction allows for the clearer visualization of structures hidden underneath.
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Evaluation of the quality of CT images acquired with smart metal artifact reduction software ; volume:13 ; number:1 ; year:2018 ; pages:155-162 ; extent:8
Open life sciences ; 13, Heft 1 (2018), 155-162 (gesamt 8)
- Creator
-
Zhou, Peng
Zhang, Chunling
Gao, Zhen
Cai, Wangshu
Yan, Deyue
Wei, Zhaolong
- DOI
-
10.1515/biol-2018-0021
- URN
-
urn:nbn:de:101:1-2409201642276.416762929895
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:24 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Zhou, Peng
- Zhang, Chunling
- Gao, Zhen
- Cai, Wangshu
- Yan, Deyue
- Wei, Zhaolong