다발성 경화증 질환의 자기공명 T2 강조영상에서 단면 두께 변화에 따른 잡음 평가

• 영문명: Noise Level Evaluation According to Slice Thickness Change in Magnetic Resonance T2 Weighted Image of Multiple Sclerosis Disease
• 발행기관: 대한방사선과학회(구 대한방사선기술학회)
• 저자명: 홍인기(Inki Hong) 박민지(Minji Park) 강상현(Seong-Hyeon Kang) 이영진(Youngjin Lee)
• 간행물 정보: 『방사선기술과학』방사선기술과학 제44권 제4호, 327~333쪽, 전체 7쪽
• 주제분류: 의약학 > 방사선과학
• 파일형태: PDF
• 발행일자: 2021.08.30

영문 초록

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.

목차

Ⅰ. 서 론

Ⅱ. 대상 및 방법

Ⅲ. 결 과

Ⅳ. 고 찰

Ⅴ. 결 론

REFERENCES

키워드

자기공명영상 잡음 강도 단면 두께 브레인웹 시뮬레이션 프로그램 정량적 평가 Magnetic resonance imaging Noise level Slice thickness BrainWeb simulation program Quantitative evaluation