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