A note on the iterative MRI reconstruction from nonuniform k-space data
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A note on the iterative MRI reconstruction from nonuniform k-space data. / Knopp, Tobias; Kunis, Stefan; Potts, Daniel.
In: INT J BIOMED IMAGING, Vol. 2007, 2007, p. 24727.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - A note on the iterative MRI reconstruction from nonuniform k-space data
AU - Knopp, Tobias
AU - Kunis, Stefan
AU - Potts, Daniel
PY - 2007
Y1 - 2007
N2 - In magnetic resonance imaging (MRI), methods that use a non-Cartesian grid in k-space are becoming increasingly important. In this paper, we use a recently proposed implicit discretisation scheme which generalises the standard approach based on gridding. While the latter succeeds for sufficiently uniform sampling sets and accurate estimated density compensation weights, the implicit method further improves the reconstruction quality when the sampling scheme or the weights are less regular. Both approaches can be solved efficiently with the nonequispaced FFT. Due to several new techniques for the storage of an involved sparse matrix, our examples include also the reconstruction of a large 3D data set. We present four case studies and report on efficient implementation of the related algorithms.
AB - In magnetic resonance imaging (MRI), methods that use a non-Cartesian grid in k-space are becoming increasingly important. In this paper, we use a recently proposed implicit discretisation scheme which generalises the standard approach based on gridding. While the latter succeeds for sufficiently uniform sampling sets and accurate estimated density compensation weights, the implicit method further improves the reconstruction quality when the sampling scheme or the weights are less regular. Both approaches can be solved efficiently with the nonequispaced FFT. Due to several new techniques for the storage of an involved sparse matrix, our examples include also the reconstruction of a large 3D data set. We present four case studies and report on efficient implementation of the related algorithms.
KW - Journal Article
U2 - 10.1155/2007/24727
DO - 10.1155/2007/24727
M3 - SCORING: Journal article
C2 - 18385802
VL - 2007
SP - 24727
JO - INT J BIOMED IMAGING
JF - INT J BIOMED IMAGING
SN - 1687-4188
ER -
