Abstract：With the development of information technology and Internet industry, the world has entered the era of big data. The
development, mining and analysis of data are more and more widely applied, and high-quality data is increasingly demanded. At
present, experts and scholars have done a lot of research and development on artificial intelligence products in the medical field.
The research and development of AI products rely on massive medical clinical data. In order to ensure the quality of such products,
the necessary screening and cleaning from the source must be carried out to control data quality and support the follow-up product
development and verification process. We analyzed the data cleaning problem in DICOM format, developed the process of original
data cleaning and auditing, and tested it in practice. It proves that the data defects can be found effectively, which can be used for
reference in the future quality control of medical AI data sets.
郝烨，唐桥红，李佳戈，王浩，孟祥峰，任海萍. 数据清洗技术在DICOM格式医学图像质控中的应用[J]. 中国医疗设备, 2018, 33(12): 10-13.
HAO Ye, TANG Qiaohong, LI Jiage, WANG Hao, MENG Xiangfeng, REN Haiping. Study on Data Cleaning Technology in DICOM format Medical Image Quality Control. China Medical Devices, 2018, 33(12): 10-13.
