Data Truncation Artifact Reduction in MR Imaging Using a Multilayer Neural Network

IEEE Transactions on Medical Imaging

Volumn 12, Issue 1, 1993, Pages 73-77

  Yan, Hong ^a   Mao, Jintong ^b  

^a UNIVERSITY OF SYDNEY   (Australia)

^b UNIVERSITY OF FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA PROCESSING; DATA REDUCTION; IMAGE PROCESSING; IMAGE RECONSTRUCTION; MEDICAL APPLICATIONS; MEDICAL IMAGING; NEURAL NETWORKS;

DATA TRUNCATION ARTIFACT REDUCTION; MULTILAYER NEURAL NETWORKS; NONLINEAR PREDICTION;

MAGNETIC RESONANCE IMAGING;

EID: 0027569257     PISSN: 02780062     EISSN: 1558254X     Source Type: Journal    
DOI: 10.1109/42.222669     Document Type: Article

References (10)

1. A. K. Jain, Fundamentals of Digital Image Processing. Englewood Cliffs, NJ: Prentice-Hall, 1989.
2. R. W. Gerchberg, “Super-resolution through error energy reduction,” Opt. Acta, vol. 14, pp. 709–720, 1979.
3. A. Papoulis, “A new algorithm in spectral analysis and band-limited extrapolation,” IEEE Trans. Circuits Syst., vol. 22, pp. 735–742, 1975.
4. D. C. Youla and H. Webb, “Image restoration by the method of convex projection,” IEEE Trans. Med. Imag., vol. 1, pp. 81–94, 1982.
5. M. R. Smith, S. T. and Nichols, R. M. Henkelman, and M. L. Wood, “Application of autoregressive moving average parametric modeling in magnetic resonance image reconstruction,” IEEE Trans. Med. Imag., vol. 5, pp. 132–139, 1986.
6. J. F. Martin and C. F. Tirendi, “Modified linear prediction modeling in magnetic resonance imaging,” J. Magn. Reson., vol. 82, pp. 392–399, 1989.
7. E. M. Haacke, Z. Liang, and S. H. Izen, “Super resolution reconstruction through object modeling and parameter estimation,” IEEE Trans. AcoustSpeech, Signal Processing, vol. 37, pp. 592–595, 1989.
8. R. T. Constable and R. M. Henkelman, “Data extrapolation for truncation artifact removal,” Magn. Reson. Med., vol. 17, pp. 108–118, 1991.
9. M. R. Smith, S. T. Nichols, R. T. Constable, and R. M. Henkelman, “A quantitative comparison of the TERA modeling and DFT magnetic resonance image reconstruction techniques,” Magn. Reson. Med., vol. 19, pp. 1–19, 1991.
10. A. S. Weigend, B. A. Huberman, and D. E. Rumelhart, “Predicting the future: A connectionist approach,” Int. J. Neural Syst., vol. 3, pp. 193–209, 1990.