Phase 2: AI in Image Acquisition & Reconstruction

Educational Simulation

This tool demonstrates the theoretical application of AI denoising algorithms in Radiology Phase 2 workflows (Image Acquisition). It simulates the "Low Dose vs. Image Quality" trade-off that AI reconstruction aims to solve.

Concept Demonstrated: AI algorithms allow for lower radiation dose protocols by reconstructing diagnostic-quality images from noisy, low-dose raw data.

How to Use

1. Launch the Tool: [Link will go here once deployed]
2. Move the Slider: - Left: Simulates a raw low-dose acquisition (High Noise).
   • Right: Simulates the AI-reconstructed output (High Fidelity).

Disclaimer

EDUCATIONAL USE ONLY. This is a JavaScript-based visual simulation using Gaussian noise injection. It does not run a clinical Deep Learning reconstruction model (e.g., DLIR) and should not be used for diagnostic decision-making.