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http://dx.doi.org/10.7742/jksr.2021.15.1.9

Evaluation of Tendency for Characteristics of MRI Brain T2 Weighted Images according to Changing NEX: MRiLab Simulation Study  

Kim, Nam Young (Department of Radiological Science, College of Health Science, Gachon University)
Kim, Ju Hui (Department of Radiological Science, College of Health Science, Gachon University)
Lim, Jun (Department of Radiological Science, College of Health Science, Gachon University)
Kang, Seong-Hyeon (Department of Radiological Science, College of Health Science, Gachon University)
Lee, Youngjin (Department of Radiological Science, College of Health Science, Gachon University)
Publication Information
Journal of the Korean Society of Radiology / v.15, no.1, 2021 , pp. 9-14 More about this Journal
Abstract
Recently, magnetic resonance imaging (MRI), which can acquire images with good contrast without exposure to radiation, has been widely used for diagnosis. However, noise that reduces the accuracy of diagnosis is essentially generated when acquiring the MR images, and by adjusting the parameters, the noise problem can be solved to obtain an image with excellent characteristics. Among the parameters, the number of excitation (NEX) can acquire images with excellent characteristics without additional degradation of image characteristics. In contrast, appropriate NEX setting is required since the scan time increases and motion artifacts may occur. Therefore, in this study, after fixing all MRI parameters through the MRiLab simulation program, we tried to evaluate the tendency of image characteristics according to changing NEX through quantitative evaluation of brain T2 weighted images acquired by adjusting only NEX. To evaluate the noise level and similarity of the acquired image, signal to noise ratio (SNR), contrast to noise ratio (CNR), root mean square error (RMSE) and peak signal to noise ratio (PSNR) were calculated. As a result, both noise level and similarity evaluation factors showed improved values as NEX increased, while the increasing width gradually decreased. In conclusion, we demonstrated that an appropriate NEX setting is important because an excessively large NEX does not affect image characteristics improvement and cause motion artifacts due to a long scan.
Keywords
MRI; brain T2 weighted image; MRiLab simulation program; NEX; quantitative evaluation;
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