Learn about some of the key opportunities for deep learning in medical imaging, some of the current challenges, and exciting recent developments that are tackling them. We'll begin with a brief overview of medical imaging, current challenges for human observers of these images, and key applications for deep learning for improving image interpretation. We'll follow with descriptions of several specific use cases for deep learning in radiology, pathology, urology, and ophthalmology imaging, including improvements in image diagnosis that are besting state-of-the-art computerized diagnosis algorithms, approaches for visualizing and explaining to physicians what deep networks have learned to improve confidence in using the information they provide to guide decision making, and new, freely available tools to dramatically enhance the efficiency of creating new deep learning models. We'll provide links for more information about tools and information so attendees can try their hand at tackling problems in this exciting domain. Finally, we'll give a live demonstration for a portable deep learning package optimized for medical imaging.