Medical imaging diagnosis is the most assisted method to help physicians diagnose patient diseases using different imaging test modalities. In fact, Deep learning aims to simulate human cognitive functions. It providing a paradigm shift in the field of medical imaging, due to the expanding availability of medical imaging data and to the advancing deep learning techniques. In effect, deep learning algorithms have become the approach of choice for medical imaging, from image acquisition to image retrieval, from segmentation to disease prediction. In our paper, we present a review that focuses on exploring the application of deep learning in medical imaging from different perspectives.