Master's Theses & Technical Reports - Michael Lustig
5th Year M.S.
A Novel Self-Supervised Deep Learning Method for MRI Reconstruction
Frederic Wang [2024]
Berkeley MRI Shimming Tool: Online B0 Shimming using Conformal and Local DC Arrays
Robert Peltekov [2024]
DL-ZTE: Towards Deep Learning-based Methods for Dead Time Gap Recovery in Zero TE MRI
Ana Cismaru [2024]
Reference-Free Image Quality Metric for Degradation and Reconstruction Artifacts
Han Cui [2023]
Respiratory and Cardiac Motion Correction Using the Beat Pilot Tone
Katie Lamar [2023]
An Automated Control System for Beat Pilot Tone in MRI
Jordan Grelling [2022]
Intensity Based Visualization of Pulmonary Biomarkers on Ultrashort Echo Time (UTE) MRI
Darren Hsu [2022]
Deep Learning Applications in Computational MRI: A Thesis in Two Parts
Sukrit Arora [2021]
Detection of Node Pore Sensing Signals
Maxwell Lin-He [2021]
Integrating a Localized B0 Shim Array into a Solenoid Transmit-Receive Coil for Permanent Magnet Scanners
Celine Veys [2021]
Local B0 Shim Array Integrated onto a Solenoid TRX Coil for Permanent Magnet Scanners
Rafael Calleja [2021]
M.S.
Synthesizing Complex-Valued MRI data from Magnitude-Only Images
nikhil deveshwar [2023]
gNUFFTW: Auto-Tuning for High-Performance GPU-Accelerated Non-Uniform Fast Fourier Transforms
Teresa Ou [2017]
Node-Pore Coded Coincidence Correcting Microfluidic Channel Framework: Code Design and Sparse Deconvolution
Michael Kellman [2017]
Concentric Rings K-space Trajectory for Hyperpolarized C-13 MR Spectroscopic Imaging
Wenwen Jiang [2014]