MLOPS: Protect and Redact Private Information in DICOM Images
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This video tutorial demonstrates how to detect and protect sensitive information in DICOM medical images that are subject to privacy regulations like GDPR, PII, or HIPAA in the healthcare industry. Learn to implement anonymization techniques using Microsoft Presidio specifically for DICOM images, while also exploring additional C# tools for working with both DICOM and FHIR formats. The 44-minute guide provides practical implementation steps for medical data privacy protection in machine learning operations. Note that the accompanying notebook and code resources are available exclusively to paying subscribers through contacting mlengineerchannel@gmail.com.
Syllabus
MLOPS: Protect and Redact Private Information in DICOM Images #datascience #machinelearning
Taught by
The Machine Learning Engineer