Optimization and Engineering

, Volume 5, Issue 4, pp 485–502 | Cite as

Rapid, Embeddable Design Method for Spiral Magnetic Resonance Image Reconstruction Resampling Kernels

  • Christopher Kumar Anand
  • Tamás Terlaky
  • Bixiang Wang
Article

Abstract

After formulating the design problem for Resampling Kernels used in Magnetic Resonance Spiral Image Reconstruction, we show that an iterative Gauss-Seidel-type interior-point optimization method is suitable (fast and light-weight) for embedded uses. In contrast to previous practice, we directly optimize a computationally efficient, piecewise-linear kernel rather than an analytic function (Kaiser-Bessel). We also optimize our kernels for worst-case (infinity-norm) signal aliasing, rather than the usual proxy energy function (2-norm) minimization. In numerical simulations of undesirable near-frequency systematic noise the new kernel significantly outperforms a conventional Kaiser-Bessel-based solution.

magnetic resonance imaging spiral imaging regridding non-uniform Fourier transform interior point method 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Christopher Kumar Anand
    • 1
  • Tamás Terlaky
    • 1
  • Bixiang Wang
    • 1
  1. 1.Department of Computer ScienceMcMaster UniversityHamilton, OntarioCanada

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