51 citations · 54 across the 5 of their papers we have counts for
6 papers
ORION-CMR: On-scanner Reporting with Integrated Foundation Model for End-to-End Cardiac MRI Analysis and Interpretation
Omer Burak Demirel, Kelly K. Horst, Alessio Perazzolo +15
Cardiovascular magnetic resonance (CMR) provides comprehensive cardiac assessment but remains underutilized because of the complexity of acquisition, post-processing, and interpret…
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction
Omer Burak Demirel, Burhaneddin Yaman, Logan Dowdle +7
High spatial and temporal resolution across the whole brain is essential to accurately resolve neural activities in fMRI. Therefore, accelerated imaging techniques target improved…
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning
Omer Burak Demirel, Burhaneddin Yaman, Logan Dowdle +7
Functional MRI (fMRI) is commonly used for interpreting neural activities across the brain. Numerous accelerated fMRI techniques aim to provide improved spatiotemporal resolutions.…
Multi-Mask Self-Supervised Learning for Physics-Guided Neural Networks in Highly Accelerated MRI
Burhaneddin Yaman, Hongyi Gu, Seyed Amir Hossein Hosseini +5
Self-supervised learning has shown great promise due to its capability to train deep learning MRI reconstruction methods without fully-sampled data. Current self-supervised learnin…
Calibration-Free Relaxation-Based Multi-Color Magnetic Particle Imaging
Yavuz Muslu, Mustafa Utkur, Omer Burak Demirel +1
Magnetic Particle Imaging (MPI) is a novel imaging modality with important applications such as angiography, stem cell tracking, and cancer imaging. Recently, there have been effor…
A Blind Deconvolution Technique Based on Projection Onto Convex Sets for Magnetic Particle Imaging
Onur Yorulmaz, Omer Burak Demirel, Yavuz Muslu +3
Magnetic Particle Imaging (MPI) is an emerging imaging modality that maps the spatial distribution of magnetic nanoparticles. The x-space reconstruction in MPI results in highly bl…