Merve Gülle

Fast MRI for All: Bridging Access Gaps by Training without Raw Data

Physics-driven deep learning (PD-DL) approaches have become popular for improved reconstruction of fast magnetic resonance imaging (MRI) scans. Though PD-DL offers higher acceleration rates than...

Consistency Models for Fast MRI Using Regularization by Denoising

Robust Outer Volume Subtraction with Deep Learning Ghosting Detection for Highly-Accelerated Real-Time Dynamic MRI

A Convex Compressibility-Inspired Unsupervised Loss Function for Physics-Driven Deep Learning Reconstruction

Fast MRI for All: Bridging Access Gaps by Training without Raw Data

PnP-CM: Consistency Models as Plug-and-Play Priors for Inverse Problems

High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI

Highly-Accelerated High-Resolution Multi-Echo fMRI Using Self-Supervised Physics-Driven Deep Learning Reconstruction