Speaker
Description
Deep learning has shown great potential in improving and accelerating the entire medical imaging workflow, from image acquisition to interpretation. This talk will focus on the recent advances of deep learning in medical imaging, from the reconstruction of accelerated signals to automatic quantification of clinically useful information. The talk will describe how model-based deep learning can be used for reconstruction of accelerated MRI and will discuss its applications to fast dynamic cardiac MRI cine imaging. It will also show the utility of deep learning for fast analysis of medical images, with a particular focus on image registration and motion tracking. Finally, it will briefly discuss about the open challenges and opportunities of AI in medical imaging.
