AFIDs Clinical

AFIDs framework applied to clinical imaging data.
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Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
• Repository Structure
4. Contributing
5. License
6. Contact
7. Acknowledgements

About The Project

This companion repository is for the article Application of the anatomical fiducials framework to a clinical dataset of patients with Parkinson’s disease.

Built With

• Python version: 3.8
• Matlab version: vR2018b

Getting Started

To get a local copy up and running follow these simple steps.

Prerequisites

• No Prerequisites required

Installation

1. In a terminal, clone the repo by running:

   git clone https://github.com/greydongilmore/afids-clinical.git

2. Change into the project directory (update path to reflect where you stored this project directory):

   cd /home/user/Documents/Github/afids-clinical

3. Install the required Python packages:

   python -m pip install -r src/python/requirements.txt

Usage

• Ideal AFIDs coordinates in templates (/data/fid_standards):
  • MNI152NLin2009bAsym
  • PD25
  • deepbrain7t
• Linear and non-linear transforms of fcsv to MNI are at: /data/input_fid_MNI_linear_combined
  • Linear .fcsv files end with _lin.fcsv
  • Non-linear .fcsv files end with _nlin.fcsv

Repository Structure

The repository has the following scheme:

├── README.md
├── LICENSE.txt
├── data
|   ├── fid_standards
|   ├── input_fid_MNI_linear_combined
|   ├── input_fid_native
|   ├── OASIS-1
|   └── demographics.tsv
├── manuscript
|   ├── afids_glass_brain.html                      # Interactive glass brain plot of all AFIDs
|   └── final_figures                               # Final manuscript figures
├── results
|   ├── avg_fcsv
|   └── plots
└── src
    ├── matlab
    |    ├── Fids_analysis.m                        # AFIDs analysis in patient space 
    |    ├── Fids_analysis_fmriprep.m               # AFIDs analysis using fmriprep results
    |    ├── Fids_analysis_mni.m                    # AFIDs analysis in MNI space 
    |    └── Fids_distance.m                        
    └── python
        ├── antsApplyH5TransformsToSlicerFCSV.py    # applies full ANTS transform to fcsv file of markups points using the **antsApplyTransformsToPoints** ANTS command 
        ├── antsApplyLinearTransformToSlicerFCSV.py # applies linear component of ANTS transform to fcsv file of markups points using the **antsApplyTransformsToPoints** ANTS command 
        ├── apply_transform.py                      # to be run within 3D Slicer Python interactor - applies transform to all input fcsv files
        ├── Fids_analysis.py                        # manuscript analysis and figures
        ├── registration_decoupling.py              # code used to decouple the linear and non-linear components of the ANTS transform using the **CompositeTransformUtil** ANTS command
        └── requirements.txt

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under the MIT License. See LICENSEfor more information.

Contact

• Mohamad Abbass - mohamad.abbass26@gmail.com
• Greydon Gilmore - @GilmoreGreydon - greydon.gilmore@gmail.com

Project Link: https://github.com/greydongilmore/afids-clinical

Acknowledgements

• README format was adapted from Best-README-Template