Optimizing SwiftMR Protocols for Diverse Applications

The whitepaper by Geunu Jeong, MD, Head of SwiftMR Research at AIRS Medical Inc., introduces SwiftMR™, a deep learning-based technology designed to enhance MRI quality by improving the signal-to-noise ratio (SNR) and spatial resolution without increasing scan times or introducing artifacts.

This comprehensive whitepaper primarily focuses on developing customized protocols for SwiftMR to meet diverse user requirements. It provides detailed guidance on adjusting sequence parameters to tailor the technology to various clinical needs. The main objective is to demonstrate how strategic optimization of imaging protocols can maximize the benefits of SwiftMR™, showcasing how modifications in acquisition parameters can lead to significant improvements in scan time reduction, spatial resolution, SNR, contrast, and artifacts.