FlexiMRIprep

This pipeline provides a versatile framework for applying preprocessing methods to MRI images. With this pipeline, you can easily apply various stages of preprocessing to a large number of MRI images.

Table of Contents

• Hardware Requirements
• Installation
• Usage
• File Structure
• License

Hardware Requirements

This pipeline does not require a graphics card or CUDA!

Installation

Instructions on how to set up the development environment.

This pipeline is fully tested in Python 3.10. To use this pipeline, it is recommended to install using the install.sh script. If you use the installation file, there is no need to change the default Python version. The desired Python version is installed locally.

chmod +x install.sh
./install.sh
source .venv/bin/activate

At this stage, you need to install the following tools. If it is not possible to access them through the terminal, please add their paths in the environment file.

• ANTS
• Nighres

Template Downloads

Please download the following files and extract them into the Template folder.

1. Download the file mni_icbm152_lin_nifti.zip from this link and extract it into the Template folder. For more information, visit this page.

2. Download the file mni_icbm152_nlin_asym_09c_nifti.zip from this link and extract it into the Template folder. For more information, visit this page.

Note

In some cases, it may be necessary to reinstall the SimpleITK package at the final step. Use the following command to reinstall:

python3 -m pip install SimpleITK==2.1.1.2 # pip install SimpleITK==2.1.1.2

Usage

To use the preprocessing pipeline, run the main.py script with the appropriate options:

usage: main.py [-h] [-m MASK] [-b BASE_IMAGE] [-lm LIST_MODALITIES]
               [-i READ_DIR] [-o WRITE_DIR] [-s1 REGISTRATION_FSL_STEP]
               [-s2 REGISTRATION_ANTS_STEP] [-s3 SKULL_STRIPPING]
               [-s4 BIAS_CORRECTION_N4_STEP] [-s5 MULTIPLYING_STEP]
               [-s6 FUZZY_CMEANS_SEGMENTATION_STEP] [-p PARENT_DIR] [-s STEPS]

options:
  -h, --help            show this help message and exit
  -m MASK, --mask MASK  name of the mask file (.nii.gz)
  -b BASE_IMAGE, --base_image BASE_IMAGE
                        The first modality for making skull mask and Co-Registration
  -lm LIST_MODALITIES, --list_modalities LIST_MODALITIES
                        The list of modalities
  -i READ_DIR, --read_dir READ_DIR
                        Input path of the patient directory
  -o WRITE_DIR, --write_dir WRITE_DIR
                        Output path of the patient directory
  -s1 REGISTRATION_FSL_STEP, --registration_FSL_step REGISTRATION_FSL_STEP
                        Change the parameters for registration step (e.g., '-s:1')
  -s2 REGISTRATION_ANTS_STEP, --registration_ANTS_step REGISTRATION_ANTS_STEP
                        Change the parameters for registration step (e.g., '-s:1')
  -s3 SKULL_STRIPPING, --skull_stripping SKULL_STRIPPING
                        Change the parameters for skull stripping (e.g., '-s:1')
  -s4 BIAS_CORRECTION_N4_STEP, --bias_correction_n4_step BIAS_CORRECTION_N4_STEP
                        Change the parameters for bias correction (e.g., '-f:0.4')
  -s5 MULTIPLYING_STEP, --Multiplying_step MULTIPLYING_STEP
                        Multiplying images (e.g., '-d:3')
  -s6 FUZZY_CMEANS_SEGMENTATION_STEP, --fuzzy_cmeans_segmentation_step FUZZY_CMEANS_SEGMENTATION_STEP
                        Fuzzy-cmeans segmentation of MRI files (e.g., '-d:3')
  -p PARENT_DIR, --parent_dir PARENT_DIR
                        The path of the main directory
  -s STEPS, --steps STEPS
                        Choose the order of the pipeline (1. Registration (FSL), 2. Registration (ANTs), 3. Skull stripping, 4. Bias correction-N4)

If you want the calculations to be distributed across the processor to increase speed, use these commands:

ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS=8
export ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS

An example of using this pipeline:

python main.py -s "422256" -m "non" -lm "" -i "input" -o "output" -s2 r:1

File Structure

The following is an example of the directory structure for the input files, output files, and pipeline scripts:

MRI-Preprocessing-Pipeline/
├── input/
│   ├── patient1/
│   │   └── FLAIR.nii.gz
│   ├── patient2/
│   │   └── FLAIR.nii.gz
│   └── .../
├── output/
│   ├── patient1/
│   │   └── FLAIR.nii.gz
│   ├── patient2/
│   │   └── FLAIR.nii.gz
│   └── .../
├── src/
│   ├── bias_correction_n4_step.py
│   ├── fuzzy_cmeans_segmentation_step.py
│   ├── multiply_Images_step.py
│   ├── registration_ANTs_step.py
│   ├── registration_step.py
│   ├── skull_stripping_step.py
│   └── Template
│       ├── mni_icbm152_wm_tal_nlin_asym_09c.nii
│       ├── mni_icbm152_t2_tal_nlin_asym_09c.nii
│       ├── icbm_avg_152_t1_tal_lin.nii.gz
│       └── ...
├── install.sh
├── main.py
├── README.md
├── requirements.txt
└── LICENSE.md

License

This project is licensed under the GPL-3.0 license - see the LICENSE file for details.