Deep-Learning-Based Motion Correction For Quantitative Cardiac MRI
Alfredo De Goyeneche, Shuyu Tang, N. Okai Addy, Bob S. Hu, William R. Overall, Juan M. Santos
International Society for Magnetic Resonance in Medicine Annual Meeting 2021
One-Click Spine MRI
Alfredo De Goyeneche, Eric Peterson, J. Jason He, N. Okai Addy, Juan M. Santos
Medical Imaging Meets NeurIPS Workshop at NeurIPS 2019
Automatic Scanning: Can Computing Be Leveraged to Extend Scanning Capabilities?
Vikas Gulani, Krishna Nayak, C. C. Tchoyoson Lim, Lawrence Wald
Monday Parallel 1 Live Q&A Monday, 10 August 2020, 15:15 – 16:00 UTC Moderators: Sonal Krishan & Andrew Webb
Automatic Scanning: Can Computing Be Leveraged to Extend Scanning Capabilities?
Juan M. Santos
International Society for Magnetic Resonance in Medicine Annual Meeting 2020
HeartVista Closes $8.65M Series A Financing Led by Khosla Ventures
HeartVista Raises $8.65M to Expand One Click, AI-guided MRI Platform
HeartVista Raises $8.65 Million to Democratize MRI Technology
HeartVista Powers Up with $8.7 Million Series A
HeartVista Closes $8.65M Series A Financing Led by Khosla Ventures
Funding Round to Fuel New Musculoskeletal and Neural Products, Expand Internationally, and Deepen Strategic Alliances with the World’s Leading Cardiology Centers
How AI is Driving the Future of Cardiac MR
Last September, a study published in the journal, Circulation: Cardiovascular Imaging, reported that analysis of cardiac MR scans using automated machine learning was significantly faster and had comparable accuracy to human interpretation by trained cardiologists. In other words, an AI algorithm could read a cardiac MR in four seconds!
