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A tool for NEMA NU 2-2018 Image Quality analysis.

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Tests Code style: black License: Apache-2.0 Python Git Download Git Release

ChameleonIQ: Nema-aware Image Quality Tool for Python

This project is a Python-based tool for the automated analysis of PET image quality based on the NEMA NU 2-2018 standard, specifically focusing on Section 7.4.1.

Features

  • Calculates Percent Contrast (Q_H,j), Percent Background Variability (N_j), and Accuracy of Corrections (ΔC_lung,i).
  • Utilizes 3D Regions of Interest (ROIs) based on the NEMA Body Phantom.
  • Loads nii image data with user-defined dimensions and voxel spacing.
  • Automatic postions of ROIs on given centers

Project Structure

nema-analysis-tool
├── data
├── documentation
├── src
│  ├── config
│  ├── nema_merge
│  ├── nema_quant
│  └── nema_quant_iter
└── tests
  • Config: configuration files to run the tool
  • Data: Data for testing and logos used for PDF reports
  • Documentation: Documentation, wikis and how to install the tool
  • nema_merge: scripts for creating fusing of individuals runs
  • nema_quant: scripts for individuals test runs
  • nema_quant_iter: scripts for a iteration based analysis

How to get Started?

Read these:

Additional information:

License

This project is licensed under the Apache Lincese 2.0 - see the LICENSE.md file for details.

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