메뉴 건너뛰기




Volumn , Issue , 2009, Pages 393-396

Real-time dynamic MR image reconstruction using Kalman Filtered Compressed Sensing

Author keywords

Compressed Sensing; Dynamic MRI; Kalman Filtered Compressed Sensing

Indexed keywords

BRAIN IMAGES; COMPRESSED SENSING; DYNAMIC MRI; KALMAN FILTERED COMPRESSED SENSING; MEASUREMENT MATRIX; MEDICAL IMAGES; MR IMAGES; REAL APPLICATIONS; REAL-TIME DYNAMICS; SIMULATION DATA; SPARSE SIGNALS; TIME SEQUENCES;

EID: 70349445473     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (55)

References (9)
  • 2
    • 36849088522 scopus 로고    scopus 로고
    • Sparse mri: The application of compressed sensing for rapid mr imaging
    • Dec
    • M. Lustig, D. Donoho, and J. M. Pauly, "Sparse mri: The application of compressed sensing for rapid mr imaging," Magnetic Resonance in Medicine, vol. 58(6), pp. 1182-1195, Dec. 2007.
    • (2007) Magnetic Resonance in Medicine , vol.58 , Issue.6 , pp. 1182-1195
    • Lustig, M.1    Donoho, D.2    Pauly, J.M.3
  • 6
    • 70349441904 scopus 로고    scopus 로고
    • k-t focuss: A general compressed sensing framework for high resolution dynamic mri
    • Dec
    • H. Jung, K. Sung, K. S. Nayak, E. Y. Kim, and J. C. Ye, "k-t focuss: a general compressed sensing framework for high resolution dynamic mri," Magnetic Resonance in Medicine, vol. 35, No. 6, 2313-2351, Dec.2007.
    • (2007) Magnetic Resonance in Medicine , vol.35 , Issue.6 , pp. 2313-2351
    • Jung, H.1    Sung, K.2    Nayak, K.S.3    Kim, E.Y.4    Ye, J.C.5
  • 7
    • 33645712308 scopus 로고    scopus 로고
    • Just relax: Convex programming methods for identifying sparse signals in noise
    • March
    • Joel A.Tropp, "Just relax: Convex programming methods for identifying sparse signals in noise," IEEE Trans. on Info. Th., vol. 52, no. 3, March.2006.
    • (2006) IEEE Trans. on Info. Th , vol.52 , Issue.3
    • Tropp, J.A.1
  • 9
    • 47849114121 scopus 로고    scopus 로고
    • The dantzig selector: Statistical estimation when p is much larger than n
    • E. Candes and T. Tao, "The dantzig selector: statistical estimation when p is much larger than n," Annals of Statistics, 2006.
    • (2006) Annals of Statistics
    • Candes, E.1    Tao, T.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.