Medical image analysis is an interdisciplinary field of comprehensive medical imaging and analyzing, whose goal is to recognize disease diagnosis and lesion area through the related computer vision technology. Benefiting from the continuous development of the convolutional neural networks, medical image analysis based on deep learning has become a research hot spot. In this paper, based on in-depth literature research of results and progress in recent years, we mainly analyze the domestic and foreign research status of Medical Imaging in various application fields such as detection, segmentation and registration. We further compare the performance of representative methods on common data sets, and summary the existing challenges in deep learning-based medical image analysis. Finally, we discuss the solutions to these problems and predict the future development of medical image analysis tasks.