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KMID : 0357520210440040327
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Journal of Radiological Science and Technology
2021 Volume.44 No. 4 p.327 ~ p.333
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Noise Level Evaluation According to Slice Thickness Change in Magnetic Resonance T2 Weighted Image of Multiple Sclerosis Disease
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Hong In-Ki
Park Min-Ji
Kang Seong-Hyeon
Lee Young-Jin
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Abstract
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Magnetic resonance imaging(MRI) uses strong magnetic field to image the cross-section of human body and has excellent image quality with no risk of radiation exposure. Because of above-mentioned advantages, MRI has been widely used in clinical fields. However, the noise generated in MRI degrades the quality of medical images and has a negative effect on quick and accurate diagnosis. In particular, examining a object with a detailed structure such as brain, image quality degradation becomes a problem for diagnosis. Therefore, in this study, we acquired T2 weighted 3D data of multiple sclerosis disease using BrainWeb simulation program, and used quantitative evaluation factors to find appropriate slice thickness among 1, 3, 5, and 7 mm. Coefficient of variation and contrast to noise ratio were calculated to evaluate the noise level, and root mean square error and peak signal to noise ratio were used to evaluate the similarity with the reference image. As a result, the noise level decreased as the slice thickness increased, while the similarity decreased after 5 mm. In conclusion, as the slice thickness increases, the noise is reduced and the image quality is improved.
However, since the edge signal is lost due to overlapped signal, it is considered that selecting appropriate slice thickness is necessary.
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KEYWORD
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Magnetic resonance imaging, Noise level, Slice thickness, BrainWeb simulation program, Quantitative evaluation
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