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Abstract #4178

Variable-Density 3D Cones Trajectory Design with Compressed Sensing Reconstruction

Nii Okai Addy1, Holden H. Wu, 12, Dwight G. Nishimura1

1Electrical Engineering, Stanford University, Stanford, CA, United States; 2Cardiovascular Medicine, Stanford University, Stanford, CA, United States

 

Keywords

achieve achieved adding addition additional adjusting aliasing allows amount anisotropic artifact artifacts aspects axial axis bandwidth best blurring bottom card cardiovascular choice choosing circumferential clarity closely combines components compressed computer concentrated cone cones constant coronal cosine create creates decrease decreasing densities density dependence design designed desired determined distance dual efficient effort electrical engineering equivalent essentially exist fast fewer field fitting function functions good grad gradient gradients graphics gurney hence improved incorporated increasing individually initial introduces inversely iteration iterations leaves linear match middle moderate motion noticeable optimization options origin originally oscillate oscillating parallel pattern phantom pipe preferable prescribed presence processors produced programming proportional quality radial readout readouts receiver reconstructed reconstruction reconstructions reduce reducing reduction regularization remove required requirements requiring respective respectively robustness roughly sample sampling satisfy scanner segment sensing sets simulated simulation simulations slight slightly space spacing specified spectral spiral subtle surface trajectories trajectory traverse uniform uniformly variable variation various view visually