clabtoolkit 0.4.2

A comprehensive toolkit for neuroimaging data processing and analysis

A comprehensive Python toolkit for neuroimaging data processing and analysis, specifically designed for working with brain connectivity data, BIDS datasets, and various neuroimaging formats.

• Free software: Apache Software License 2.0

• Documentation: https://clabtoolkit.readthedocs.io

• Source Code: https://github.com/connectomicslab/clabtoolkit

• Python versions: 3.9+

Installation

Install from PyPI:

pip install clabtoolkit

For development installation:

git clone https://github.com/connectomicslab/clabtoolkit.git
cd clabtoolkit
pip install -e .[dev]

Features

BIDS Tools (clabtoolkit.bidstools)

• BIDS dataset validation and manipulation

• Entity extraction from BIDS filenames

• Conversion between BIDS formats

• Metadata handling for neuroimaging datasets

Connectivity Tools (clabtoolkit.connectivitytools)

• Brain connectivity matrix analysis

• Network-based statistics

• Graph theory metrics computation

• Connectivity visualization utilities

FreeSurfer Tools (clabtoolkit.freesurfertools)

• FreeSurfer output parsing and processing

• Surface-based analysis utilities

• Cortical thickness and morphometry tools

• Integration with FreeSurfer workflows

Image Processing Tools (clabtoolkit.imagetools)

• Neuroimaging data I/O operations

• Image registration and transformation

• Quality control and preprocessing utilities

• Multi-modal image processing

Parcellation Tools (clabtoolkit.parcellationtools)

• Brain parcellation scheme handling

• Region-of-interest (ROI) extraction

• Atlas-based analysis tools

• Custom parcellation creation

Surface Tools (clabtoolkit.surfacetools)

• Surface mesh processing and analysis

• Cortical surface manipulation

• Surface-based statistics

• Visualization of surface data

DWI Tools (clabtoolkit.dwitools)

• Diffusion-weighted imaging analysis

• Tractography processing utilities

• DTI and advanced diffusion modeling

• White matter analysis tools

Quality Control Tools (clabtoolkit.qcqatools)

• Automated quality assessment

• Image artifact detection

• Quality metrics computation

• Reporting and visualization

Visualization Tools (clabtoolkit.visualizationtools)

• Brain visualization utilities

• Interactive plotting capabilities

• Publication-ready figures

• Multi-modal data visualization

Quick Start

import clabtoolkit.bidstools as bids
import clabtoolkit.connectivitytools as conn

# Load BIDS configuration
config = bids.load_bids_json()

# Extract entities from BIDS filename
entities = bids.str2entity("sub-01_ses-M00_T1w.nii.gz")
print(entities)  # {'sub': '01', 'ses': 'M00', 'suffix': 'T1w', 'extension': 'nii.gz'}

# Process connectivity data
# conn_matrix = conn.load_connectivity_matrix("path/to/connectivity.mat")

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository

2. Create your feature branch (git checkout -b feature/amazing-feature)

3. Commit your changes (git commit -m 'Add some amazing feature')

4. Push to the branch (git push origin feature/amazing-feature)

5. Open a Pull Request

Testing

Run tests with:

pytest

Run tests with coverage:

pytest --cov=clabtoolkit

Changelog

See HISTORY.rst for a detailed changelog.

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.