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 Configuration Guide). 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

Common Tasks