Chen Qin

Deep Learning Meets Medical Imaging: From Signals to Clinically Useful Information

Machine Learning has shown great potential in improving the entire medical imaging workflow, from image acquisition to disease treatment. This talk will focus on the recent advances of machine learning in medical imaging, from the reconstruction of signals to 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 one of its applications to dynamic cardiac MRI cine imaging. It will also show the clinical utility of deep learning for the analysis of medical images, with a particular focus on image registration for myocardial motion tracking. Finally, it will briefly discuss about the open challenges and the future of AI in medical imaging.