Abstract

MR image acquisition and reconstruction in the era of deep learning

Florian Knoll
New York University

Recent basic science developments in optimization and deep learning, as well as widespread access to powerful computing resources and large datasets have the potential to change the way medical imaging is performed. Using the common theme of inverse problems and variational optimization, I will discuss the potential to make MR imaging faster, easier to use, more patient friendly and accessible, and to obtain new information. I will cover both methodological developments as well as clinical translation and validation and discuss ongoing developments as well as currently open research questions.