Abstract
Identification and re-identification are two major security and privacy threats to medical imaging data. De-identification in DICOM medical data is essential to preserve the privacy of patients’ Personally Identifiable Information (PII) and requires a systematic approach. However, there is a lack of sufficient detail regarding the de-identification process of DICOM attributes, for example, what needs to be considered before removing a DICOM attribute. In this paper, we first highlight and review the key challenges in the medical image data de-identification process. In this paper, we develop a two-stage de-identification process for CT scan images available in DICOM file format. In the first stage of the de-identification process, the patient’s PII—including name, date of birth, etc., are removed at the hospital facility using the export process available in their Picture Archiving and Communication System (PACS). The second stage employs the proposed DICOM de-identification tool for an exhaustive attribute-level investigation to further de-identify and ensure that all PII has been removed. Finally, we provide a roadmap for future considerations to build a semi-automated or automated tool for the DICOM datasets de-identification.
Subject
Health Information Management,Health Informatics,Health Policy,Leadership and Management
Reference40 articles.
1. Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints
2. Top 5 Use Cases for Artificial Intelligence in Medical Imaging
https://healthitanalytics.com/news/top-5-use-cases-for-artificialintelligence-in-medical-imaging
3. Providing Integrity, Authenticity, and Confidentiality for Header and Pixel Data of DICOM Images
4. SOAD: Securing oncology EMR by anonymizing DICOM images;Shahbaz;Proceedings of the 2013 11th International Conference on Frontiers of Information Technology,2013
5. A Developer Driven Framework for Security and Privacy in the Internet of Medical Things;Treacy,2020
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