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  • 标题:A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis
  • 本地全文:下载
  • 作者:Arsalan Shahid ; Mehran H. Bazargani ; Paul Banahan
  • 期刊名称:Healthcare
  • 电子版ISSN:2227-9032
  • 出版年度:2022
  • 卷号:10
  • 期号:5
  • DOI:10.3390/healthcare10050755
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要: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.
  • 关键词:enprivacy preservationde-identificationDICOMmedical image analytics
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