- Quick summary
- A Python-based Dynamic multi-bed PET simulation and reconstruction framework with analytical modeling of system matrix, capable of incorporating various degrees of PSF modeling.
- Version
- 1.0.1.1
-
Necessary packages
- NiBabel (To read and write NIfTI files)
- scikit-image
- SciPy
- sklearn
-
Start-up
- To start the project you need to run the file SimulateDynamicMulibedFDG.py
-
Configurations (config.json)
- You can change various parameters in the config file such as:
- Dimensions (xdim, ydim, zdim)
- Number of frames
- Axial and trans axial Field of View
- Iterations
- Subsets
- Scan Duration
- VCT Sensitivity
- Attenuation units (if mu_map is in units of 1/voxel attenuation, that's the default assumption. If it's in units of 1/mm, then one needs to multiply it by bins-size)
- Additional configurations can be added to automate and ease the process of simulation.
- You can change various parameters in the config file such as:
-
Image Comparison
- File CompareOutputImages.py calculates the following metrics between MATLAB and Python generated files:
- Mean Squared Error (MSE)
- Peak Signal to Noise Ratio (PSNR)
- Structural Similarity Index (SSIM)
- This file is run independently.
- File CompareOutputImages.py calculates the following metrics between MATLAB and Python generated files:
This code was developed by Nolla Sherifi ([email protected]) between October 2023 and March 2024 at the Technical University of Munich.