The talk will focus on the use of deep learning techniques for the discovery and quantification of clinically useful information from medical images. The talk will describe how deep learning can be used for the reconstruction of medical images from undersampled data, image super-resolution, image segmentation and image classification. It will also show the clinical utility of applications of deep learning for the interpretation of medical images in applications such as brain tumour segmentation, cardiac image analysis and applications in neonatal and fetal imaging. Finally, it will be discussed how deep learning may change the future of medical imaging.