Getting Started =============== What You Need ------------- - Python 3.11+ - A PET reconstruction in NIfTI format (``.nii`` or ``.nii.gz``) - Scanner parameters (voxel spacing, acquisition time) - Phantom activity concentrations Quick Installation ------------------ Install ChameleonIQ using pip:: pip install ChameleonIQ Verify Installation ~~~~~~~~~~~~~~~~~~~ Test your installation by running:: chameleoniq_quant --help Your First Analysis ------------------- Command Line ~~~~~~~~~~~~ 1) Create a YAML config (see :doc:`guides/configuration`). Or run the ROI tool to generate the config interactively:: chameleoniq_roi input.nii.gz --standard NU_2_2018 2) Run a single analysis:: chameleoniq_quant input.nii.gz --config config.yaml --output results.txt 3) Optional: enable visualizations:: chameleoniq_quant input.nii.gz --config config.yaml --output results.txt --save-visualizations Python API ~~~~~~~~~~ Programmatic analysis:: from pathlib import Path from config.defaults import get_cfg_defaults from nema_quant.io import load_nii_image from nema_quant.phantom import NemaPhantom from nema_quant.analysis import calculate_nema_metrics # Load configuration and image cfg = get_cfg_defaults() image_data, affine = load_nii_image(Path('image.nii.gz'), return_affine=True) # Extract image properties image_dims = image_data.shape voxel_spacing = ( float(abs(affine[0, 0])), float(abs(affine[1, 1])), float(abs(affine[2, 2])) ) # Initialize phantom and analyze phantom = NemaPhantom(cfg, image_dims, voxel_spacing) results, lung_results = calculate_nema_metrics(image_data, phantom, cfg) Next Steps ---------- - **Install**: :doc:`installation` for detailed setup - **Run**: :doc:`usage` for CLI and workflows - **Configure**: :doc:`guides/configuration` for YAML details - **Understand**: :doc:`guides/how_it_works` for the pipeline Common Tasks ~~~~~~~~~~~~ .. toctree:: :maxdepth: 1 guides/batch_processing