𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Optimization of sensitivity encoding with arbitrary k-space trajectories

✍ Scribed by Mark Bydder; Joanna E. Perthen; Jiang Du

Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
525 KB
Volume
25
Category
Article
ISSN
0730-725X

No coin nor oath required. For personal study only.

✦ Synopsis

Sensitivity encoding (SENSE) is a magnetic resonance technique that unifies gradient and receive coil encoding. SENSE reconstructs the image by solving a large, ill-conditioned inverse problem, which generally requires regularization and preconditioning. The present study suggests a simple heuristic for determining the regularization parameter. Also discussed are the use of density weighting and intensity correction as preconditioners and the role that coil sensitivity estimation has in regularization. A modification to the intensity correction is proposed for use with a phase constraint.

📜 SIMILAR VOLUMES

Advances in sensitivity encoding with ar
Advances in sensitivity encoding with arbitrary k-space trajectories
✍ Klaas P. Pruessmann; Markus Weiger; Peter Börnert; Peter Boesiger 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 482 KB

## Abstract New, efficient reconstruction procedures are proposed for sensitivity encoding (SENSE) with arbitrary __k__‐space trajectories. The presented methods combine gridding principles with so‐called conjugate‐gradient iteration. In this fashion, the bulk of the work of reconstruction can be p

A statistical approach to SENSE regulari
A statistical approach to SENSE regularization with arbitrary k-space trajectories
✍ Leslie Ying; Bo Liu; Michael C. Steckner; Gaohong Wu; Min Wu; Shi-Jiang Li 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 867 KB

## Abstract SENSE reconstruction suffers from an ill‐conditioning problem, which increasingly lowers the signal‐to‐noise ratio (SNR) as the reduction factor increases. Ill‐conditioning also degrades the convergence behavior of iterative conjugate gradient reconstructions for arbitrary trajectories.

Parallel spectroscopic imaging reconstru
Parallel spectroscopic imaging reconstruction with arbitrary trajectories using k-space sparse matrices
✍ Meng Gu; Chunlei Liu; Daniel M. Spielman 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 409 KB

## Abstract Parallel imaging reconstruction has been successfully applied to magnetic resonance spectroscopic imaging (MRSI) to reduce scan times. For undersampled k‐space data on a Cartesian grid, the reconstruction can be achieved in image domain using a sensitivity encoding (SENSE) algorithm for

Optimal design of k-space trajectories u
Optimal design of k-space trajectories using a multi-objective genetic algorithm
✍ Brian M. Dale; Jonathan S. Lewin; Jeffrey L. Duerk 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 435 KB 👁 1 views

## Abstract Spiral, radial, and other nonrectilinear __k‐__space trajectories are an area of active research in MRI due largely to their typically rapid acquisition times and benign artifact patterns. Trajectory design has commonly proceeded from a description of a simple shape to an investigation

Improvement of spiral MRI with the measu
Improvement of spiral MRI with the measured k-space trajectory
✍ Xiaoping Ding; Jean Tkach; Paul Ruggieri; John Perl; Thomas Masaryk 📂 Article 📅 1997 🏛 John Wiley and Sons 🌐 English ⚖ 529 KB

## Abstract The k‐space trajectory of a spiral imaging sequence was measured with a self‐encoding technique. The image quality improved dramatically when reconstructed with the measured k‐space trajectory. There were substantial artifacts in images reconstructed with the derived k‐space trajectory