22 citations · 76 across the 16 of their papers we have counts for
6 papers · 1 filter
High-fidelity Direct Contrast Synthesis from Magnetic Resonance Fingerprinting
Ke Wang, Mariya Doneva, Jakob Meineke +6
Magnetic Resonance Fingerprinting (MRF) is an efficient quantitative MRI technique that can extract important tissue and system parameters such as T1, T2, B0, and B1 from a single…
Accelerated Motion Correction with Deep Generative Diffusion Models
Brett Levac, Sidharth Kumar, Ajil Jalal +1
Magnetic Resonance Imaging (MRI) is a powerful medical imaging modality, but unfortunately suffers from long scan times which, aside from increasing operational costs, can lead to…
An untrained deep learning method for reconstructing dynamic magnetic resonance images from accelerated model-based data
Kalina P. Slavkova, Julie C. DiCarlo, Viraj Wadhwa +5
The purpose of this work is to implement physics-based regularization as a stopping condition in tuning an untrained deep neural network for reconstructing MR images from accelerat…
Polynomial Preconditioners for Regularized Linear Inverse Problems
Siddharth Srinivasan Iyer, Frank Ong, Xiaozhi Cao +4
This work aims to accelerate the convergence of proximal gradient methods used to solve regularized linear inverse problems. This is achieved by designing a polynomial-based precon…
MIMO Channel Estimation using Score-Based Generative Models
Marius Arvinte, Jonathan I Tamir
Channel estimation is a critical task in multiple-input multiple-output (MIMO) digital communications that substantially effects end-to-end system performance. In this work, we int…
Differentiable Rendering for Synthetic Aperture Radar Imagery
Michael Wilmanski, Jonathan Tamir
There is rising interest in differentiable rendering, which allows explicitly modeling geometric priors and constraints in optimization pipelines using first-order methods such as…