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

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.

Release files for clabtoolkit 0.4.5

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