Earticle

초록

영어

In this study, an angiography equipment is used to measure changes in image quality in fluoroscopy and non-subtraction angiography images depending on the magnification of each image. For this purpose, the noise level is measured by setting a region of interest (ROI) of the same size for each image through the MATLAB program, and the evaluation factors are coefficient of variation (COV), contrast to noise ratio (CNR), and signal to noise ratio (SNR) was used. As a result, the mean COV was measured about 4 to 7 times lower, the mean CNR was measured about 2 to 3 times higher, and the mean SNR was measured about 3 to 7 times higher in the non-subtraction contrast image than in the fluoroscopy image. Also, for both images, when the intensifier size is set to the smallest (at maximum magnification), the mean COV is decreased by about 4.9 times, the mean CNR is increased by about 2.9 times, and the mean SNR is increased by about 5.0 times in fluoroscopy images. And in the case of non-subtraction angiography images, the mean COV decreased by about 3.9 times, the mean CNR increased by about 3.4 times, and the mean SNR increased by about 3.9 times. In conclusion, it was confirmed that the noise of the non-subtraction angiography image is less than that of the fluoroscopy image, and that the higher the magnification of both images, the better the image quality.

한국어

본 연구에서는 혈관조영장비로 투시영상 및 비감산조영영상에서의 각 영상별 확대율에 따른 화질변화를 측정하고자 하였다. 이를 위해 MATLAB 프로그램을 통해 각 영상별 동일 크기의 관심영역을 설정하여 noise level을 측정하였으며, 평가인자로는 coefficient of variation(COV), contrast to noise ratio(CNR), 그리고 signal to noise ratio(SNR) 이 사용되었다. 결과적으로 투시영상에 비해 비감산조영영상에서 평균 COV는 약 4~7배 낮게 측정되었고, 평균 CNR은 약 2~3배 높게 측정되었으며, 평균 SNR은 약 3~7배 높게 측정되어 상대적으로 화질이 좋음을 확인하였다. 또한 두 영상 모두에서 영상을 최대로 확대시켰을 때, 투시영상의 경우 평균 COV는 약 4.9배 감소하였으며, 평균 CNR은 약 2.9배, 그리고 평균 SNR은 약 5.0배 증가하였고, 비감산조영영상의 경우 평균 COV는 약 3.9배 감소하였으며, 평균 CNR은 약 3.4배, 그리고 평균 SNR은 약 3.9배 증가하였다. 결론적으로 투시영상에 비해 비감산조영영상에서, 그리고 확대율이 높을수록 화질이 향상됨을 확인하였다.

목차

Abstract
Ⅰ. 서론
Ⅱ. 대상 및 방법
1. 영상 획득 및 실험장비
2. 영상의 정량적 평가
Ⅲ. 결과 및 고찰
Ⅳ. 결론
Ⅴ. 참고문헌
요약

키워드

저자

• Kanghyeon Seo [ 서강현 | Department of Radiology, Hallym Hospital/Department of Radiological Science, College of Health Science, Gachon University ]
• Yunhee Mo [ 모윤희 | Department of Radiology, Buchon ST. Mary’s Hospital ]
• Seong-hyeon Kang [ 강성현 | Department of Radiological Science, College of Health Science, Gachon University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  대한디지털의료영상학회논문지 [Korean Journal of Digital Imaging in Medicine]

• 간기

  연3회

• pISSN

  1976-7641

• 수록기간

  1995~2025

• 십진분류

  KDC 510 DDC 610