메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Ji Sung Jang (Asan Medical Center) Ho Beom Lee (Asan Medical Center) Seok Hwan Yoon (Seoul National University Hospital) Min Cheol Jeon (Daejeon Health Institute of Technology) Seong Ho Kim (Daejeon Health Institute of Technology)
저널정보
한국자기학회 Journal of Magnetics Journal of Magnetics Vol.27 No.2
발행연도
2022.6
수록면
217 - 222 (6page)
DOI
10.4283/JMAG.2022.27.2.217

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
This study aimed to assess the effect of zero-filling interpolation (ZIP) and various spatial resolutions on quality assurance (QA). Two important variables for the assessments of magnetic resonance image quality were included with recommended acceptance criteria: high-contrast spatial resolution and low-contrast object detectability with reference limits. All acquired data were divided into two groups: group A (without ZIP) and group B (with ZIP). The spatial resolutions of both images of T1-weighted and T2-weighted imaging in both directions fulfilled the American College of Radiology (ACR) criterion in group B. The observed high-contrast spatial resolution values were significantly different between the two groups up to a matrix size of 320 × 320 (p < 0.05). On the other hand, with a matrix size ≥ 384 × 384, no significant differences between the two groups were observed in terms of high-contrast spatial resolution (p > 0.05). For low-contrast object detectability, the total number of measured spokes in all groups fulfilled the ACR criterion. However, the low-contrast object detectability values without ZIP tended to decrease as the matrix size decreased. The use of ZIP can improve high-contrast spatial resolution and low-contrast object detectability while reducing image blurriness.

목차

1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusion
References

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0