no code implementations • 22 Sep 2022 • Guanhua Wang, Jon-Fredrik Nielsen, Jeffrey A. Fessler, Douglas C. Noll
Optimizing 3D k-space sampling trajectories for efficient MRI is important yet challenging.
1 code implementation • 2 May 2022 • Melissa W. Haskell, Jon-Fredrik Nielsen, Douglas C. Noll
In magnetic resonance imaging (MRI), inhomogeneity in the main magnetic field used for imaging, referred to as off-resonance, can lead to image artifacts ranging from mild to severe depending on the application.
2 code implementations • 27 Jan 2021 • Guanhua Wang, Tianrui Luo, Jon-Fredrik Nielsen, Douglas C. Noll, Jeffrey A. Fessler
Though trained with neural network-based reconstruction, the proposed trajectory also leads to improved image quality with compressed sensing-based reconstruction.
2 code implementations • 24 Aug 2020 • Tianrui Luo, Douglas C. Noll, Jeffrey A. Fessler, Jon-Fredrik Nielsen
This paper proposes a new method for joint design of radiofrequency (RF) and gradient waveforms in Magnetic Resonance Imaging (MRI), and applies it to the design of 3D spatially tailored saturation and inversion pulses.
1 code implementation • 24 Sep 2018 • Gopal Nataraj, Jon-Fredrik Nielsen, Mingjie Gao, Jeffrey A. Fessler
In vivo and ex vivo experiments demonstrate that MESE MWF and DESS PERK ff estimates are quantitatively comparable measures of WM myelin water content.
no code implementations • 6 Oct 2017 • Gopal Nataraj, Jon-Fredrik Nielsen, Clayton Scott, Jeffrey A. Fessler
This paper introduces a fast, general method for dictionary-free parameter estimation in quantitative magnetic resonance imaging (QMRI) via regression with kernels (PERK).