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Magnetic Resonance Image restoration

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Abstract

We introduce a novel technique for Magnetic Resonance Image (MRI) restoration, using a physical model (spin equation) and corresponding basis images. We determine the basis images (proton density and nuclear relaxation times) from the MRI data and use them to obtain excellent restorations.

Magnetic Resonance Images depend nonlinearly on proton density,ρ, two nuclear relaxation times,T 1 andT 2, and two control parameters, TE and TR. We model images a Markov random fields and introduce two maximuma posteriori (MAP) restorations; quadratic smoothing and a nonlinear technique. We also introduce a novel method of global optimization necessary for the nonlinear technique.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, North Carolina State University, 27695-7911, Raleigh, NC, USA

    Stephen J. Garnier & Griff L. Bilbro

  2. U.S. Army Research Office, Research Triangle Park, NC, USA

    James W. Gault

  3. Department of Radiology, Bowman-Gray School of Medicine, Wake Forest University, NC, USA

    Wesley E. Snyder

Authors
  1. Stephen J. Garnier
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  2. Griff L. Bilbro
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  3. James W. Gault
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  4. Wesley E. Snyder
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Garnier, S.J., Bilbro, G.L., Gault, J.W. et al. Magnetic Resonance Image restoration. J Math Imaging Vis 5, 7–19 (1995). https://doi.org/10.1007/BF01250250

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