Aegis
A localized medical imaging de-identification engine that handles the cleansing of identifiable metadata in DICOM files, OCR detection of burned-in pixel text, and NER entity classification. It outputs converted files and a queue for manual review, ensuring that protected health information (PHI) does not cross the local trust boundary.
Timeline (last 90 days)
Aegis is a local de-identification engine that, combined with Claude's MCP tool-calling capability, forms a privacy-first medical imaging AI Agent architecture, in which the model is only responsible for process orchestration while image pixels and PHI always remain within the local trust boundary.
For DICOM files, Aegis cleans identifiable metadata and checks for burned-in text in pixels that metadata rules cannot remove; OCR detects candidate text regions, NER helps classify sensitive entities, and policy rules determine which content needs to be masked, whitelisted or sent for manual review.
Outputs allowed to flow from Aegis to Claude include aggregate counts, job IDs, cleaned filenames, state transitions and review-needed flags; prohibited outputs include image bytes, pixel crops, OCR text, DICOM tag values, raw exception payloads and re-identification keys.
During development, synthetic samples should be used instead of real patient data to validate the tools, and both successful and uncertain results should be checked, comparing reported counts against the generated audit rows.
Both Vaultwarden and official Bitwarden support TOTP-based two-step verification and can be used with authenticator apps such as Aegis and Authy.
All Facts (5)
Aegis is a local de-identification engine that, combined with Claude's MCP tool-calling capability, forms a privacy-first medical imaging AI Agent architecture, in which the model is only responsible for process orchestration while image pixels and PHI always remain within the local trust boundary.
50%UnverifiedFor DICOM files, Aegis cleans identifiable metadata and checks for burned-in text in pixels that metadata rules cannot remove; OCR detects candidate text regions, NER helps classify sensitive entities, and policy rules determine which content needs to be masked, whitelisted or sent for manual review.
50%UnverifiedOutputs allowed to flow from Aegis to Claude include aggregate counts, job IDs, cleaned filenames, state transitions and review-needed flags; prohibited outputs include image bytes, pixel crops, OCR text, DICOM tag values, raw exception payloads and re-identification keys.
50%UnverifiedDuring development, synthetic samples should be used instead of real patient data to validate the tools, and both successful and uncertain results should be checked, comparing reported counts against the generated audit rows.
50%UnverifiedBoth Vaultwarden and official Bitwarden support TOTP-based two-step verification and can be used with authenticator apps such as Aegis and Authy.
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