Musculoskeletal (MSK) imaging is a research field that remains lots of technical and clinical challenges. The recent development of Artificial Intelligence, particularly Deep Learning (DL), has demonstrated great potentials to resolve such challenges. This talk will present a technical overview of Deep Learning in MSK imaging and discuss some recent DL applications that successfully translate new learning-based approaches into performance improvement in MSK imaging workflow. One major aim is to draw tightly connections between fundamental DL concepts and technical challenges in MSK imaging. Topics will cover from rapid image acquisition, reconstruction, and MR parameter mapping, to image post-processing such as image segmentation and translation in MSK imaging. The talk will conclude with a discussion of open problems in DL that are particularly relevant to MSK imaging and the potential challenges and opportunities in this emerging field.