{"ID":2886780,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.02177","arxiv_id":"2508.02177","title":"Deep classification algorithm for De-identification of DICOM medical images","abstract":"Background : De-identification of DICOM (Digital Imaging and Communi-cations in Medicine) files is an essential component of medical image research. Personal Identifiable Information (PII) and/or Personal Health Identifying Information (PHI) need to be hidden or removed due to legal reasons. According to the Health Insurance Portability and Accountability Act (HIPAA) and privacy rules, also full-face photographic images and any compa-rable images are direct identifiers and are considered protected health information that also need to be de-identified. Objective : The study aimed to implement a method that permit to de-identify the PII and PHI information present in the header and burned on the pixel data of DICOM. Methods : To execute the de-identification, we implemented an algorithm based on the safe harbor method, defined by HIPAA. Our algorithm uses input customizable parameter to classify and then possibly de-identify individual DICOM tags. Results : The most sensible information, like names, history, personal data and institution were successfully recognized. Conclusions : We developed a python algorithm that is able to classify infor-mation present in a DICOM file. The flexibility provided by the use of customi-zable input parameters, which allow the user to customize the entire process de-pending on the case (e.g., the language), makes the entire program very promis-ing for both everyday use and research purposes. Our code is available at https://github.com/rtdicomexplorer/deep_deidentification.","short_abstract":"Background : De-identification of DICOM (Digital Imaging and Communi-cations in Medicine) files is an essential component of medical image research. Personal Identifiable Information (PII) and/or Personal Health Identifying Information (PHI) need to be hidden or removed due to legal reasons. According to the Health Ins...","url_abs":"https://arxiv.org/abs/2508.02177","url_pdf":"https://arxiv.org/pdf/2508.02177v1","authors":"[\"Bufano Michele\",\"Kotter Elmar\"]","published":"2025-08-04T08:21:18Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false,"code_links":[{"ID":611347,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2886780,"paper_url":"https://arxiv.org/abs/2508.02177","paper_title":"Deep classification algorithm for De-identification of DICOM medical images","repo_url":"https://github.com/rtdicomexplorer/deep_deidentification","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}