128 citations · 331 across the 14 of their papers we have counts for
4 papers · 1 filter
Optimal Sampling & Reconstruction: Theory and Applications
Justin P. Haldar
The optimization of MRI data sampling and image reconstruction methods has been a priority for the MRI community since the very early days of the field. Designing an "optimal" meth…
Fast Sub-millimeter Diffusion MRI using gSlider-SMS and SNR-Enhancing Joint Reconstruction
Justin P. Haldar, Qiuyun Fan, Kawin Setsompop
We evaluate a new approach for achieving diffusion MRI data with high spatial resolution, large volume coverage, and fast acquisition speed. A recent method called gSlider-SMS enab…
LORAKI: Autocalibrated Recurrent Neural Networks for Autoregressive MRI Reconstruction in k-Space
Tae Hyung Kim, Pratyush Garg, Justin P. Haldar
We propose and evaluate a new MRI reconstruction method named LORAKI that trains an autocalibrated scan-specific recurrent neural network (RNN) to recover missing k-space data. Met…
Linear Predictability in MRI Reconstruction: Leveraging Shift-Invariant Fourier Structure for Faster and Better Imaging
Justin P. Haldar, Kawin Setsompop
Over the past several decades, many different types of computational imaging approaches have been proposed for improving MRI. In this paper, we provide an overview of methods that…