Desensitization and Cleaning Technology of CT Image of Parotid Tumor based on DICOM

Abstract

Abstract CT image data are widely used in model training and data mining in the fields of medical image processing and medical big data analysis. Sensitive information on the data set needs to be desensitized before use. Traditional CT image data desensitization often wipe Remove most of the patient’s identification information. The data has not been cleaned, and the quality and analytical value of the data can’t be guaranteed after desensitization. In order to solve the privacy protection and data quality problems of DICOM-based image datasets during use, this paper uses symmetric encryption, numerical transformation and invalidation desensitization strategies to desensitize CT images of parotid tumor CT images based on DICOM. The desensitized encrypted data are decrypted to determine the true identity of the patient for data cleaning. Data cleaning is performed on the desensitized and decrypted data according to the formulated process. While meeting the desensitization standard to protect the privacy and safety of patients, the method of this paper greatly guarantees the quality, statistical characteristics and analytical value of the desensitized data set, and provide a feasible solution to the safe use and quality control of CT image data sets in the future.