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Getting started with image de-identification with Presidio

Presidio provides a simple way to de-identify image data by detecting and anonymizing personally identifiable information (PII). This guide shows you how to get started with image de-identification using Presidio's Python packages.

Presidio has two main modules for image de-identification: General purpose, and specifically for DICOM (medical) images.

Simple flow - Python package

  1. Install presidio-image-redactor

    pip install presidio-image-redactor

  2. Redact PII from image

    from presidio_image_redactor import ImageRedactorEngine
from PIL import Image

image = Image.open(path_to_image_file)

redactor = ImageRedactorEngine()
redactor.redact(image=image)

  1. Install presidio-image-redactor

    pip install presidio-image-redactor

  2. Redact text PII from DICOM image

    import pydicom
from presidio_image_redactor import DicomImageRedactorEngine

# Set input and output paths
input_path = "path/to/your/dicom/file.dcm"
output_dir = "./output"

# Initialize the engine
engine = DicomImageRedactorEngine()

# Option 1: Redact from a loaded DICOM image
dicom_image = pydicom.dcmread(input_path)
redacted_dicom_image = engine.redact(dicom_image, fill="contrast")

# Option 2: Redact from DICOM file
engine.redact_from_file(input_path, output_dir, padding_width=25, fill="contrast")

# Option 3: Redact from directory
engine.redact_from_directory("path/to/your/dicom", output_dir, padding_width=25, fill="contrast")

Simple flow - Docker container

Presidio provides a Docker containers that you can use to de-identify image data.

  1. Download Docker image
docker pull mcr.microsoft.com/presidio-image-redactor
  1. Run container
docker run -d -p 5003:3000 mcr.microsoft.com/presidio-image-redactor
  1. Use the API
curl -XPOST "http://localhost:5003/redact" -H "content-type: multipart/form-data" -F "image=@img.png" -F "data=\"{'color_fill':'255'}\"" > out.png

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