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.

Please use this cite when using the sofware:

 Ulin-Briseno, E. (2026). ChameleonIQ (Version 3.0.1) [Computer software]. https://github.com/EdAlita/ChameleonIQ

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

How to get Started?

Read these:

• Installation instructions
• Usage instructions
• How it works?

Additional information:

• What will change?

License

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

Acknowledgements

ChameleonIQ is an open-source project developed as part of my research activities at the Institute for Institute for Instrumentation in Molecular Imaging (i3M). I gratefully acknowledge the support of the Detectors for Molecular Imaging Laboratory (DMIL), i3M, and the Spanish National Research Council (CSIC). The i3M is a joint research center established in 2010 by the Universitat Politècnica de València (UPV) and CSIC, located on the Vera Campus in Valencia, Spain.