An Image Domain Low Rank Model for Calibrationless Reconstruction of Images with Slowly Varying Phase
Evan Levine 1,2 and Brian Hargreaves 2
Electrical Engineering, Stanford University,
Stanford, CA, United States,
Stanford University, Stanford, CA, United States
Calibrationless constrained reconstruction methods
employing low-rank models have attracted recent
attention due to their high accuracy and sampling
flexibility. Recently, k-space-based methods LORAKS and
P-LORAKS were proposed for calibrationless
reconstruction of images with slowly varying phase from
single-channel and multi-channel parallel imaging data.
For the same settings, we propose an image-domain
locally low rank model to exploit slow phase variation.
The model can be used to augment other image-domain
constrained reconstruction models to exploit slow phase
variation with little overhead.
This abstract and the presentation materials are available to members only;
a login is required.