6 citations · 12 across the 6 of their papers we have counts for
3 papers · 1 filter
Quantitative Susceptibility Inversion Through Parcellated Multiresolution Neural Networks and K-Space Substitution
Juan Liu, Andrew S. Nencka, L. Tugan Muftuler +3
Purpose: Quantitative Susceptibility Mapping (QSM) reconstruction is a challenging inverse problem driven by poor conditioning of the field to susceptibility transformation. State-…
Application of a k-Space Interpolating Artificial Neural Network to In-Plane Accelerated Simultaneous Multislice Imaging
Nikolai J. Mickevicius, Eric S. Paulson, L. Tugan Muftuler +1
Purpose: The goal of this work is to extend the capabilities of RAKI, a k-space interpolating neural network, to reconstruct high-quality images from in-plane accelerated simultane…
Build-A-FLAIR: Synthetic T2-FLAIR Contrast Generation through Physics Informed Deep Learning
Andrew S. Nencka, Andrew Klein, Kevin M. Koch +7
Purpose: Magnetic resonance imaging (MRI) exams include multiple series with varying contrast and redundant information. For instance, T2-FLAIR contrast is based upon tissue T2 dec…