Tutorials¶

Interactive Jupyter notebooks demonstrating qmri workflows.

Try Online¶

Launch the tutorials directly in your browser with Binder:

Available Notebooks¶

1. ADC Fitting Workflow¶

File: 01_adc_fitting_workflow.ipynb

Learn how to:

Generate synthetic DWI data with known ADC
Fit ADC using different methods
Visualise fitting results and error maps
Understand clinical ADC values

2. T1 Mapping with Synthetic Data¶

File: 02_t1_mapping_synthetic.ipynb

Learn how to:

Generate inversion recovery (IR) data
Compare general vs classical IR models
Use variable TR (VTR) method
Create multi-voxel T1 maps

3. ASL Perfusion Quantification¶

File: 03_asl_perfusion_quantification.ipynb

Learn how to:

Generate pCASL control and label images
Understand the General Kinetic Model
Explore transit time effects
Visualise perfusion maps

4. Method Comparison Benchmark¶

File: 04_method_comparison_benchmark.ipynb

Learn how to:

Compare LLS, WLLS, and IWLLS fitting
Run Monte Carlo simulations
Analyse bias and variance trade-offs
Benchmark different b-value protocols

5. Noise Sensitivity Analysis¶

File: 05_noise_sensitivity_analysis.ipynb

Learn how to:

Compare Gaussian vs Rician noise
Determine SNR requirements
Optimise acquisition design
Quantify parameter uncertainty

Running Locally¶

Clone the repository and run the notebooks locally:

# Clone repository
git clone https://github.com/gold-standard-phantoms/qmri.git
cd qmri

# Install dependencies
uv sync

# Start JupyterLab
uv run jupyter lab examples/jupyter/

Prerequisites¶

The tutorials assume familiarity with:

Python and NumPy basics
MRI physics fundamentals
Jupyter notebook interface

No prior qmri experience is required.