Mu C C, Li G
Department of Oral and Maxillofacial Radiology, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Laboratory for Digital and Material Technology of Stomatology & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China.
Zhonghua Kou Qiang Yi Xue Za Zhi. 2019 Jul 9;54(7):492-497. doi: 10.3760/cma.j.issn.1002-0098.2019.07.011.
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.
计算机硬件的发展使得医学影像数据能够快速积累。深度学习在医学影像数据分析中展现出巨大潜力,并开创了机器学习的一个新领域。本文首先介绍了常用的深度学习模型,然后总结了深度学习在医学影像的检测、分类、诊断、分割、识别等方面的应用。提出了深度学习在口腔颌面放射学及口腔医学其他学科中的应用。最后,本文讨论了深度学习在医学影像研究中存在的问题。