Paper
26 June 2023 Intelligent management of maintenance information of magnetic resonance imaging equipment
Xin-yi Liu, Xiang-xiang Luo, Hui Yuan, Wen-han Hu, Yan-ze Xue, Feng Li, Ding-hui Liu, Yu-yang Xu, Ya-jun Liu
Author Affiliations +
Proceedings Volume 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023); 127141I (2023) https://doi.org/10.1117/12.2683541
Event: Third International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 2023, Sanya, China
Abstract
Imaging examination plays an important role in the clinical diagnosis and treatment of diseases. Magnetic Resonance Imaging (MRI) is one of the imaging examinations, which has been widely used in clinic clinical practice. The non-Cartesian Radial sampling method is used to obtain the image data, and it is interpolated to the uniform Cartesian coordinates using the gridding algorithm and then reconstructed. Finally, using the ability of GPU parallel computing to improve the efficiency of the grid, shorten the reconstruction time, and expect to accelerate the image reconstruction speed. The experimental results also show that under the same conditions of other external conditions, compared with the CPU reconstruction, the acceleration ratio of GPU reconstruction has reached more than 12 times.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xin-yi Liu, Xiang-xiang Luo, Hui Yuan, Wen-han Hu, Yan-ze Xue, Feng Li, Ding-hui Liu, Yu-yang Xu, and Ya-jun Liu "Intelligent management of maintenance information of magnetic resonance imaging equipment", Proc. SPIE 12714, International Conference on Computer Network Security and Software Engineering (CNSSE 2023), 127141I (26 June 2023); https://doi.org/10.1117/12.2683541
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KEYWORDS
Image restoration

Reconstruction algorithms

Magnetic resonance imaging

Medical image reconstruction

Medical imaging

Data acquisition

Sampling rates

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