The Body Magnetic Resonance (BMR) Group develops and applies MRI to improve clinical care. We focus on breast MRI, abdominal MRI, MRI of osteoarthritis and MRI near metallic implants, with links between basic science, clinical imaging and industry. BMR is part of the Radiological Sciences Lab, Department of Radiology, School of Medicine, at Stanford University. Most of our students are in Electrical Engineering, Bioengineering, and Mechanical Engineering.
Diffusion-Weighted DESS with a 3D Cones Trajectory for Non-Contrast-Enhanced Breast MRI
In this work a novel diffusion-weighted method, DW-DESS-Cones, is developed and characterized in vivo for the MRI of breast cancer without a contrast injection.
Multi-Shot DWI of the Breast with MUSE and shot-LLR Reconstructions
This manuscript presents a clinical breast MRI study that investigates the performance of single-shot DWI and multi-shot DWI reconstructed by two different techniques (MUSE and Shot-LLR).
A Framework for Prospective Deployment of Deep Learning in MRI
Recent years have seen large advances in new artificial intelligence (AI) techniques for improving the current status of medical imaging, and specifically, magnetic resonance imaging (MRI).
Accelerated Multi-Shot DWI Reconstruction Using an Unrolled Network with U-Net as Priors
In this work, we accelerate and improve the reconstruction of multi-shot diffusion-weighted MRI by an unrolled pipeline, in which the presumed regularization term is replaced by a U-Net.
Diagnostic Accuracy of 5-Minute Knee MRI Using AI Image Quality Enhancement
Despite advances in accelerating MRI scans, diagnostic knee MRI protocols typically require upwards of 30 minutes of scanner time, which fundamentally limits patient throughput.