5 citations · 10 across the 4 of their papers we have counts for
4 papers
Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction
Yaşar Utku Alçalar, Mehmet Akçakaya
Physics-driven deep learning (PD-DL) models have proven to be a powerful approach for improved reconstruction of rapid MRI scans. In order to train these models in scenarios where…
Deep Learning Assisted Outer Volume Removal for Highly-Accelerated Real-Time Dynamic MRI
Merve Gülle, Sebastian Weingärtner, Mehmet Akçakaya
Real-time (RT) dynamic MRI plays a vital role in capturing rapid physiological processes, offering unique insights into organ motion and function. Among these applications, RT cine…
Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problems
Yaşar Utku Alçalar, Mehmet Akçakaya
Diffusion models have emerged as powerful generative techniques for solving inverse problems. Despite their success in a variety of inverse problems in imaging, these models requir…
Non-Cartesian Self-Supervised Physics-Driven Deep Learning Reconstruction for Highly-Accelerated Multi-Echo Spiral fMRI
Hongyi Gu, Chi Zhang, Zidan Yu +3
Functional MRI (fMRI) is an important tool for non-invasive studies of brain function. Over the past decade, multi-echo fMRI methods that sample multiple echo times has become popu…