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). However, despite these advances, there have been few instances of successful prospective clinical applications of artificial intelligence for MRI. In this manuscript, we broadly categorize the different applications of AI in MRI and provide a framework for important considerations and challenges for prospectively deploying these promising tools in the clinic to enhance patient care.
Chaudhari AS, Sandino CM, Cole EK, Larson DB, Gold GE, Vasanawala SS, Lungren MP, Hargreaves BA, Langlotz CP. Prospective deployment of deep learning in MRI: A framework for important considerations, challenges, and recommendations for best practices. J Magn Reson Imaging. 2020 Aug 24. doi: 10.1002/jmri.27331. Online ahead of print.
An example of one of three general use-cases for deep learning and convolutional neural networks in MRI.
