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Optimizing three‐dimensional (3D) k‐space sampling trajectories is important for efficient MRI yet presents a challenging computational problem. This work proposes a generalized framework for optimizing 3D non‐Cartesian sampling patterns via… Click to show full abstract
Optimizing three‐dimensional (3D) k‐space sampling trajectories is important for efficient MRI yet presents a challenging computational problem. This work proposes a generalized framework for optimizing 3D non‐Cartesian sampling patterns via data‐driven optimization.
Keywords:
optimization three;
cartesian sampling;
three dimensional;
stochastic optimization;
non cartesian
Journal Title: Magnetic Resonance in Medicine
Year Published: 2023
Link to full text (if available)
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Journal Title: Magnetic Resonance in Medicine
Year Published: 2023
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!