지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2012.10
- 수록면
- 1,103 - 1,107 (5page)
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초록· 키워드
오류제보하기
MRI is a breakthrough technology in medical diagnosis, but has a critical disadvantage of slow processing. Among the techniques used to accelerate the process of conventional MRI, SENSitivity Encoding (SENSE) is the most popular one. Also, the development of Compressed Sensing (CS) method has contributed to decrease the processing time of MRI. Both CS and SENSE accelerate conventional MRI by reducing the number of collected data and the combination of the two techniques can tremendously accelerate MRI setting time. In this paper, we propose a method combining the two techniques to accelerate conventional MRI, named p-CS. This method first uses CS to reconstruct a set of aliased images with a field of view (FOV) in each coil and applies the basic SENSE algorithm to produce the final full image. The empirical results show that signal-to-noise ratio (SNR) of the image obtained by this method is larger than that those of other methods.
목차
Abstract
1. INTRODUCTION
2. SENSITIVITY ENCODING AND COMPRESSED SENSING
3. PROPOSED METHOD
4. EXPERIMENT RESULTS
5. CONCLUSION
REFERENCES
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