SIDF: A Desensitization Framework for Sensitive Information in Chinese Medical Report Images

Medical report images have become the main information resource in intelligent medical treatment, online consultation, and medical research. While facilitating the use of relevant personnel, information security and privacy protection are particularly important. At present, there are related technologies for image desensitization or medical text desensitization, but there is a lack of research on Chinese medical report image desensitization. Thus, this paper proposes a desensitization framework for sensitive information (SIDF) in Chinese medical report images. SIDF contains five modules: sensitive information construction, text detection and text recognition, sensitive information extraction, sensitive information location, and sensitive information desensitization. Because all modules in SIDF can be flexibly designed according to specific requirements, it is convenient to use SIDF. In addition, we design an index of valid desensitization (VD) for measuring the desensitization performance of algorithms. We evaluate SIDF on the Chinese medical report images collected from Internet and private contributions. Experimental results show that our proposed desensitization framework is effective.