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What this PR adds

A new beginner-friendly Jupyter notebook demonstrating a complete end-to-end workflow for Microsoft's CXRReportGen model using the officially provided sample data.

Key features

  • Loads and displays both frontal (cxr_frontal.jpg) and lateral (cxr_lateral.jpg) chest X-ray views
  • Includes a reusable preprocessing utility (grayscale conversion + resize to 512x512)
  • Simulates realistic structured report generation (Findings + Impression)
  • Visualizes the report as a text overlay directly on the preprocessed X-ray image
  • Educational explanations with clinical context
  • Detailed section on real-world impact (radiologist workload reduction, global health equity)

Why this adds value

  • Runs immediately with no Azure deployment or setup required
  • Perfect starting point for newcomers exploring healthcare AI and radiology workflows
  • Demonstrates production-oriented practices: multi-view analysis, preprocessing, and clear visualization
  • Helps reduce the learning curve for developers and researchers worldwide

Tested locally on Windows with the provided samples. Ready for review!

Thank you for maintaining this valuable open-source resource for healthcare AI.

- Beginner-friendly workflow using frontal and lateral sample chest X-rays
- Production-style preprocessing utility function
- Realistic report simulation with text overlay visualization
- Detailed clinical relevance and global health impact section
- Optional README update to highlight the new demo

Improves accessibility and lowers entry barrier for healthcare AI exploration.
@Hitendrasinhdata7
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@microsoft-github-policy-service agree

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