37 citations · 46 across the 3 of their papers we have counts for
3 papers
eess.SP2022★ 8 cited
Latent Signal Models: Learning Compact Representations of Signal Evolution for Improved Time-Resolved, Multi-contrast MRI
Yamin Arefeen, Junshen Xu, Molin Zhang +5
Purpose: Training auto-encoders on simulated signal evolution and inserting the decoder into the forward model improves reconstructions through more compact, Bloch-equation-based r…
eess.SP2021★ 37 cited
Scan Specific Artifact Reduction in K-space (SPARK) Neural Networks Synergize with Physics-based Reconstruction to Accelerate MRI
Yamin Arefeen, Onur Beker, Jaejin Cho +3
Purpose: To develop a scan-specific model that estimates and corrects k-space errors made when reconstructing accelerated Magnetic Resonance Imaging (MRI) data. Methods: Scan-Speci…
physics.med-ph2019★ 1 cited
Accelerated spin-echo fMRI using Multisection Excitation by Simultaneous Spin-echo Interleaving (MESSI) with complex-encoded generalized SLIce Dithered Enhanced Resolution (cgSlider) Simultaneous Multi-Slice Echo-Planar Imaging
SoHyun Han, Congyu Liao, Mary Kate Manhard +8
Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared to gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large…