33 citations · 79 across the 12 of their papers we have counts for
3 papers · 1 filter
Deep Residual Network for Off-Resonance Artifact Correction with Application to Pediatric Body Magnetic Resonance Angiography with 3D Cones
David Y Zeng, Jamil Shaikh, Dwight G Nishimura +2
Purpose: Off-resonance artifact correction by deep-learning, to facilitate rapid pediatric body imaging with a scan time efficient 3D cones trajectory. Methods: A residual convolut…
Clinically Deployed Distributed Magnetic Resonance Imaging Reconstruction: Application to Pediatric Knee Imaging
Michael J. Anderson, Jonathan I. Tamir, Javier S. Turek +4
Magnetic resonance imaging is capable of producing volumetric images without ionizing radiation. Nonetheless, long acquisitions lead to prohibitively long exams. Compressed sensing…
Highly Scalable Image Reconstruction using Deep Neural Networks with Bandpass Filtering
Joseph Y. Cheng, Feiyu Chen, Marcus T. Alley +2
To increase the flexibility and scalability of deep neural networks for image reconstruction, a framework is proposed based on bandpass filtering. For many applications, sensing me…