Implemented Protocol for Data Collection

DICOM API

  • DICOM File Reception: The API receives DICOM files from institutional storage systems or through a secure interface where users can upload the files.

Data Anonymization:

  • DICOM Header Extraction: Access and read the information from the DICOM header.
  • Identification of Sensitive Data: Identify fields with potentially sensitive information that require anonymization.
  • Data Deletion or Modification: Personal data is deleted and replaced with randomly generated unique identifiers (16 characters).

Image Conversion:

  • Image Processing: Images are extracted from the DICOM file once the header anonymization is completed.
  • Conversion to PNG: Medical images are converted from their original DICOM format to PNG, facilitating handling in machine learning models.

Secure Storage (Google Cloud SafeKey):

  • Encryption at Rest: Implementation of Client-Managed Encryption (CMEK).
  • Encryption in Transit: Use of TLS, VPN, and Private Peering to protect data during transfer.
  • Key Management Encryption:
    • Google Cloud Key Management Service (KMS) for secure key management.
    • Logging and monitoring of key operations.
  • Access Controls:
    • Implementation of Identity and Access Management (IAM).
    • Application of robust security policies.
  • Audit and Compliance: Setup of Cloud Audit Logs and regular security and compliance reviews.

API Interface and Access:

  • Exposure through Google Cloud: Detail how the API interface is protected, possibly including two-factor authentication or certificates.

Compliance and Audit:

  • Regular Compliance Review: Schedule and document regular audits to ensure continuous adherence to security and privacy policies.

Relationship IMSS – EpyDiagnosis

  • Data Agreement: Confirm that there is a formal agreement detailing the rights and responsibilities of both parties in relation to the use of the data.
  • Consent Verification: Ensure that the consent process has been conducted in accordance with ethical and legal standards.
  • AI Ethics: Jointly develop with IMSS a specific ethical protocol for AI.
  • Collaborative and Multidisciplinary Review: Establish an ethics review committee and a multidisciplinary team to regularly review the project.