Structured Low-Rank Algorithms: Theory, MR Applications, and Links to Machine Learning

1 code implementation • 27 Oct 2019 • Mathews Jacob, Merry P. Mani, Jong Chul Ye

In this survey, we provide a detailed review of recent advances in the recovery of continuous domain multidimensional signals from their few non-uniform (multichannel) measurements using structured low-rank matrix completion formulation.

BIG-bench Machine Learning Low-Rank Matrix Completion

MoDL-MUSSELS: Model-Based Deep Learning for Multi-Shot Sensitivity Encoded Diffusion MRI

1 code implementation • 19 Dec 2018 • Hemant Kumar Aggarwal, Merry P. Mani, Mathews Jacob

In this work, we show that an iterative re-weighted least-squares implementation of MUSSELS alternates between a multichannel filter bank and the enforcement of data consistency.

MoDL: Model Based Deep Learning Architecture for Inverse Problems

3 code implementations • 7 Dec 2017 • Hemant Kumar Aggarwal, Merry P. Mani, Mathews Jacob

Since the forward model is explicitly accounted for, a smaller network with fewer parameters is sufficient to capture the image information compared to black-box deep learning approaches, thus reducing the demand for training data and training time.

Image Reconstruction