Variable density sampling based on physically plausible gradient waveform. Application to 3D MRI angiography

Nicolas Chauffert 1, 2 Pierre Weiss 3 Marianne Boucher 2 Sébastien Mériaux 2 Philippe Ciuciu 1, 2
1 PARIETAL - Modelling brain structure, function and variability based on high-field MRI data
NEUROSPIN - Service NEUROSPIN, Inria Saclay - Ile de France
2 NEUROSPIN - Service NEUROSPIN
3 ITAV - Institut des Technologies Avancées en sciences du Vivant
Abstract : Performing k-space variable density sampling is a popular way of reducing scanning time in Magnetic Resonance Imaging (MRI). Un-fortunately, given a sampling trajectory, it is not clear how to traverse it using gradient waveforms. In this paper, we actually show that ex-isting methods [1, 2] can yield large traversal time if the trajectory contains high curvature areas. Therefore, we consider here a new method for gradient waveform design which is based on the pro-jection of unrealistic initial trajectory onto the set of hardware con-straints. Next, we show on realistic simulations that this algorithm allows implementing variable density trajectories resulting from the piecewise linear solution of the Travelling Salesman Problem in a reasonable time. Finally, we demonstrate the application of this ap-proach to 2D MRI reconstruction and 3D angiography in the mouse brain.
Keywords : hardware constraints Compressive sensing MRI angiography gradient waveform design Variable density sampling
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Submitted on : Monday, February 23, 2015 - 3:11:14 PM
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  • HAL Id : hal-01119578, version 1
  • ARXIV : 1502.06742

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Nicolas Chauffert, Pierre Weiss, Marianne Boucher, Sébastien Mériaux, Philippe Ciuciu. Variable density sampling based on physically plausible gradient waveform. Application to 3D MRI angiography. IEEE International Symposium on Biomedical Imaging (ISBI), Apr 2015, New-York, United States. ⟨hal-01119578⟩

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