The development of computer hardware allows rapid accumulation of medical imaging data. Deep learning has shown great potential in medical imaging data analysis and establish a new area of machine learning. The commonly used deep learning models were firstly introduced in the paper, and then, summarized with the application of deep learning in the detection, classification, diagnosis, segmentation, identification of medical imaging. The application of deep learning in oral and maxillofacial radiology and other discipline of stomatology was proposed. At the end, the paper discussed the problems of deep learning in medical imaging research.

The development of computer hardware allows rapid accumulation of medical imaging data. Deep learning has shown great potential in medical imaging data analysis and establish a new area of machine learning. The commonly used deep learning models were firstly introduced in the paper, and then, summarized with the application of deep learning in the detection, classification, diagnosis, segmentation, identification of medical imaging. The application of deep learning in oral and maxillofacial radiology and other discipline of stomatology was proposed. At the end, the paper discussed the problems of deep learning in medical imaging research.