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CS-MRI Reconstruction Problem

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Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms

Part of the book series: Springer Series on Bio- and Neurosystems ((SSBN,volume 9))

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Abstract

Compressed sensing MRI (CS-MRI) seeks good quality MR image reconstruction from relatively less number of measurements than the traditional Nyquist sampling theorem. This in return increases the computational effort for reconstruction which may be dealt with some efficient solvers based on convex optimization. To reconstruct MR image from undersampled Fourier data, an underdetermined system of equations is needed to be solved with some additional information as regularization priors, like, compressibility of MR images in the spatial as well as wavelet domains.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Tezpur University, Tezpur, Assam, India

    Bhabesh Deka & Sumit Datta

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  1. Bhabesh Deka
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  2. Sumit Datta
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Correspondence to Bhabesh Deka .

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Deka, B., Datta, S. (2019). CS-MRI Reconstruction Problem. In: Compressed Sensing Magnetic Resonance Image Reconstruction Algorithms. Springer Series on Bio- and Neurosystems, vol 9. Springer, Singapore. https://doi.org/10.1007/978-981-13-3597-6_2

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  • DOI: https://doi.org/10.1007/978-981-13-3597-6_2

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-3596-9

  • Online ISBN: 978-981-13-3597-6

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