The Precomputed Functional Connectome Toolkit
Project description
pfc-toolkit
The Precomputed Functional Connectome Toolkit (pfc-toolkit) is a Python module for functional lesion network mapping using the Precomputed Functional Connectome and is distributed under the 3-Cause BSD license.
The project was started in 2019 by William Drew for his Harvard undergraduate thesis project ('21).
The project was supervised by Dr. Michael D. Fox, MD, PhD first at the Berenson-Allen Center for Noninvasive Brain Stimulation at Beth Israel Deaconess Medical Center and later at the Center for Brain Circuit Therapeutics at Brigham and Women's Hospital.
This project references work from @clin045's and @alexlicohen's connectome_quick.py from nimlab and @andreashorn's connectome.sh from LeadDBS.
The Precomputed Functional Connectome Toolkit is for research only; please do not use results from PFC Toolkit for clinical decisions.
Installation
Dependencies
pfc-toolkit requires:
- Python (>=3.6)
- NumPy
- SciPy
- Numba
- Nibabel
- Nilearn
- tqdm
- natsort
- importlib
User Installation
Install using pip
pip install -U pfc-toolkit
Usage
Development
Source code
You can check the latest sources with the command:
git clone https://github.com/thewilliamdrew/pfc-toolkit.git
Help and Support
Documentation
Documentation is located here. (WIP)
Release history Release notifications | RSS feed
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