Medical imaging data often contains patient identifiers in both metadata and visible image content. medDARE provides medical image anonymization workflows designed to remove or obscure protected health information while preserving the value of the dataset for downstream AI use.
We support de-identification across a wide range of medical imaging formats and modalities, including radiology and other clinically sensitive image datasets. Our process is built to address both structured identifiers and image-level privacy risks so your team can work with de-identified medical imaging data more confidently.
What we remove or protect
Our imaging anonymization process is designed to address:
- patient-identifying metadata
- visible names and identifiers
- dates and location details where required
- medical record and account references
- device-related identifiers
- full-face photography or identifying imagery
- other protected health information that should not remain in the dataset
Medical imaging data we can support
We can support anonymization workflows for:
- CT scans
- MRI studies
- X-ray images
- ultrasound data
- image series used in diagnostics and AI development
- other medical imaging datasets requiring de-identification
