iEEG-Recon

https://ieeg-recon.readthedocs.io/en/latest/
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iEEG-Recon is a modular pipeline for reconstructing intracranial electrode coordinates from...
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### Install VoxTool

Source: https://ieeg-recon.readthedocs.io/en/latest/module%201.html

Install the VoxTool application using pip. This is a prerequisite for running the tool from the command line.

```bash
$ pip install voxtool

```

--------------------------------

### Install iEEG-recon GUI with Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/Getting%20Started.html

Execute the installation script for the iEEG-recon GUI when using the Docker container. This script is part of the downloaded repository.

```bash
bash ieeg-recon/python/install_ieeg-recon_gui_docker.sh
```

--------------------------------

### Install iEEG-recon GUI (Python)

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/Getting%20Started.rst.txt

Run this script to install the iEEG-recon GUI for Python. Ensure you have the necessary dependencies installed.

```console
$ bash ieeg-recon/python/install_ieeg-recon_gui_m1m2.sh
```

--------------------------------

### Install iEEG-recon GUI (M1/M2)

Source: https://ieeg-recon.readthedocs.io/en/latest/Getting%20Started.html

Run the specific installation script for the iEEG-recon GUI, optimized for M1/M2 Macs. This script is located within the Python directory of the cloned repository.

```bash
bash ieeg-recon/python/install_ieeg-recon_gui_m1m2.sh
```

--------------------------------

### Run Module 2 with Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%202.rst.txt

Execute Module 2 using Docker. Ensure the example data path is absolute. The -gc flag is optional but recommended for Greedy registration.

```console
$ docker run -v absolute/path/to/exampleData:/source_data lucasalf11/ieeg_recon -s sub-RID0922 -m 2 -cs ses-clinical01 -rs ses-clinical01 -d /source_data
```

--------------------------------

### Configure MATLAB for iEEG-recon

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/Getting%20Started.rst.txt

Set the FSLDIR and ITKSNAPDIR environment variables in your MATLAB startup.m file. Update paths to match your local installation of FSL and ITK-Snap.

```MATLAB
%% in MATLAB/startup.m

% Set FSLDIR to FSL install location
setenv( 'FSLDIR', '/usr/local/fsl' );
setenv('FSLOUTPUTTYPE', 'NIFTI_GZ');
fsldir = getenv('FSLDIR');
fsldirmpath = sprintf('%s/etc/matlab',fsldir);
path(path, fsldirmpath);
clear fsldir fsldirmpath;

% Set ITKSNAPDIR to ITK-Snap install location
setenv('ITKSNAPDIR', '/Applications/ITK-SNAP.app/Contents/bin');
itksnapdir = getenv('ITKSNAPDIR');
itksnapmpath = sprintf('%s',itksnapdir);
path(path,itksnapmpath)
clear itksnapdir itksnapmpath;
```

--------------------------------

### Install VoxTool via pip

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%201.rst.txt

Install the VoxTool package using pip. This is required for command-line usage.

```console
$ pip install voxtool
```

--------------------------------

### Run VoxTool from command line

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%201.rst.txt

Launch the VoxTool application from your terminal. Ensure VoxTool is installed first.

```console
$ voxtool
```

--------------------------------

### Clone iEEG-recon Repository

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/Getting%20Started.rst.txt

Clone the iEEG-recon repository to your local machine to begin the installation process.

```console
$ git clone git@github.com:penn-cnt/ieeg-recon.git
```

--------------------------------

### Run Module 3 via Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%203.rst.txt

Execute Module 3 using Docker. Ensure the example data is mounted to the container. This command uses the default AntSpyNet atlas.

```console
$ docker run -v absolute/path/to/exampleData:/source_data lucasalf11/ieeg_recon -s sub-RID0922 -m 3 -cs ses-clinical101 -rs ses-clinical01 -d /source_data -r 2 -apn
```

--------------------------------

### Run iEEG-recon with Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/Getting%20Started.rst.txt

Execute the iEEG-recon application using Docker. Mount your data directory to the container and specify subject and session details. This example includes options for Greedy and AntsPyNet.

```console
$ docker run -v </path/to/data>:/source_data lucasalf11/ieeg_recon -s sub-<subjectID> -cs ses-<session_name> -rs ses-<session_name> -gc -m -1 -apn -r 2 -d /source_data
```

```console
$ docker run -v /Users/username/:/source_data lucasalf11/ieeg_recon -s sub-<subjectID> -cs ses-<session_name> -rs ses-<session_name> -gc -m -1 -apn -r 2 -d /source_data
```

--------------------------------

### Clone iEEG-recon Repository

Source: https://ieeg-recon.readthedocs.io/en/latest/Getting%20Started.html

Download the latest release of the iEEG-recon project from GitHub. This is a prerequisite for both Docker and manual installations.

```bash
git clone https://github.com/penn-cnt/ieeg-recon.git
```

```bash
git clone git@github.com:penn-cnt/ieeg-recon.git
```

--------------------------------

### Initialize and Run Module 3 in MATLAB

Source: https://ieeg-recon.readthedocs.io/en/latest/module%203.html

Set up subject, session, and BIDS directory variables, then initialize the ieeg_recon object and run Module 3.

```matlab
% Set up
subID = 'sub-RID0922';          % subject ID
ct_session = 'ses-clinical01';  % name of session with CT scan
mri_session = 'ses-clinical01'; % name of session with reference MRI scan
BIDS_dir = '../exampleData';    % path to BIDS directory

subject_rid922 = ieeg_recon(subID, ct_session, mri_session, BIDS_dir);

% Run Module 3
fileLocations = subject_rid0922.module3;

```

--------------------------------

### Create Conda Environment (Python)

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/Getting%20Started.rst.txt

Navigate to the python directory and create a conda environment using the provided configuration file.

```console
$ cd python
$ conda env create -f ieeg_recon_config.yml
```

--------------------------------

### Run Module 3 via Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%203.rst.txt

Execute Module 3 using Docker. Mount your data directory to \"/source_data\" within the container. Ensure all required arguments are provided.

```console
$ docker run -v absolute/path/to/exampleData:/source_data lucasalf11/ieeg_recon -s sub-RID0922 -m 3 -cs ses-clinical01 -rs ses-clinical01 -r 2 -apn -mri -d /source_data
```

--------------------------------

### Run Module 2 using Matlab

Source: https://ieeg-recon.readthedocs.io/en/latest/module%202.html

Initialize the ieeg_recon object with subject and session details, then call the module2 method to run the registration process.

```matlab
% Set up
subID = 'sub-RID0922';          % subject ID
ct_session = 'ses-clinical01';  % name of session with CT scan
mri_session = 'ses-clinical01'; % name of session with reference MRI scan
BIDS_dir = '../exampleData';    % path to BIDS directory

subject_rid922 = ieeg_recon(subID, ct_session, mri_session, BIDS_dir);

% Run Module 2
fileLocations = subject_rid922.module2;


```

--------------------------------

### Run VoxTool Application

Source: https://ieeg-recon.readthedocs.io/en/latest/module%201.html

Launch the VoxTool graphical user interface from the terminal. This command initiates the application for electrode labeling.

```bash
$ voxtool

```

--------------------------------

### Run Module 2 using Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/module%202.html

Execute Module 2 via Docker. Ensure the data path is correctly mounted. The -gc flag is optional but recommended for Greedy registration.

```bash
$ docker run -v absolute/path/to/exampleData:/source_data lucasalf11/ieeg_recon -s sub-RID0922 -m 2 -cs ses-clinical01 -rs ses-clinical01 -d /source_data

| Arguments:
| -s: subject ID
| -m: Module number
| -cs: name of session with CT scan
| -rs: name of session with reference MRI scan
| -d: path to BIDS directory
| -gc: (optional, recommended) run with Greedy


```

--------------------------------

### Run Module 3 using MATLAB

Source: https://ieeg-recon.readthedocs.io/en/latest/module%203.html

Initialize the ieeg_recon object with subject and session details, then call the module3 method to process the data. Requires setting up subject ID, session names, and BIDS directory.

```matlab
% Set up
subID = 'sub-RID0922';          % subject ID
ct_session = 'ses-clinical01';  % name of session with CT scan
mri_session = 'ses-clinical01'; % name of session with reference MRI scan
BIDS_dir = '../exampleData';    % path to BIDS directory

subject_rid922 = ieeg_recon(subID, ct_session, mri_session, BIDS_dir);

% Run Module 3
fileLocations = subject_rid922.module3;


```

--------------------------------

### Run Module 2 using Python (conda)

Source: https://ieeg-recon.readthedocs.io/en/latest/module%202.html

Execute Module 2 from the command line after activating the conda environment. The -gc flag is optional but recommended for Greedy registration.

```bash
$ conda activate ieeg_recon
$ cd python
$ python ieeg_recon.py -s sub-RID0922 -m 2 -cs ses-clinical101 -rs ses-clinical01 -d absolute/path/to/exampleData -gc

| Arguments:
| -s: subject ID
| -m: Module number
| -cs: name of session with CT scan
| -rs: name of session with reference MRI scan
| -d: path to BIDS directory
| -gc: (optional, recommended) run with Greedy


```

--------------------------------

### Run Module 2 with Matlab

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%202.rst.txt

Set up subject and session variables in Matlab and then call the ieeg_recon function to run Module 2. The 'fileLocations' variable will contain the output paths.

```matlab
% Set up
subID = 'sub-RID0922';          % subject ID
ct_session = 'ses-clinical01';  % name of session with CT scan
mri_session = 'ses-clinical01'; % name of session with reference MRI scan
BIDS_dir = '../exampleData';    % path to BIDS directory

subject_rid922 = ieeg_recon(subID, ct_session, mri_session, BIDS_dir);

% Run Module 2
fileLocations = subject_rid0922.module2;
```

--------------------------------

### Run Module 3 via Matlab

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%203.rst.txt

Set up subject and session variables in Matlab, then instantiate the ieeg_recon object and call the module3 method to run the analysis.

```matlab
% Set up
subID = 'sub-RID0922';          % subject ID
ct_session = 'ses-clinical01';  % name of session with CT scan
mri_session = 'ses-clinical01'; % name of session with reference MRI scan
BIDS_dir = '../exampleData';    % path to BIDS directory

subject_rid922 = ieeg_recon(subID, ct_session, mri_session, BIDS_dir);

% Run Module 3
fileLocations = subject_rid0922.module3;
```

--------------------------------

### Run Module 2 with Python

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%202.rst.txt

Execute Module 2 using Python after activating the 'ieeg_recon' conda environment. The -gc flag is optional but recommended for Greedy registration.

```console
$ conda activate ieeg_recon
$ cd python
$ python ieeg_recon.py -s sub-RID0922 -m 2 -cs ses-clinical101 -rs ses-clinical01 -d absolute/path/to/exampleData -gc
```

--------------------------------

### Run Module 3 with Docker and MNI Registration

Source: https://ieeg-recon.readthedocs.io/en/latest/module%203.html

Execute Module 3 using Docker, specifying subject ID, module number, session details, BIDS directory, radius, AntsPyNet atlas, and MNI registration.

```bash
$ docker run -v absolute/path/to/exampleData:/source_data lucasalf11/ieeg_recon -s sub-RID0922 -m 3 -cs ses-clinical01 -rs ses-clinical01 -r 2 -apn -mri -d /source_data

| Arguments:
| -s: subject ID
| -m: Module number
| -cs: name of session with CT scan
| -rs: name of session with reference MRI scan
| -d: path to BIDS directory
| -r: radius
| -apn: use atropos atlas from AntsPyNet
| -mni: (optional) perform MNI registration

```

--------------------------------

### Configure MATLAB Environment Variables

Source: https://ieeg-recon.readthedocs.io/en/latest/Getting%20Started.html

Set environment variables for FSLDIR and ITKSNAPDIR within MATLAB's startup.m file. This ensures that iEEG-recon can locate these essential tools. Paths may need adjustment based on your system.

```matlab
%% in MATLAB/startup.m

% Set FSLDIR to FSL install location
setenv( 'FSLDIR', '/usr/local/fsl' );
setenv('FSLOUTPUTTYPE', 'NIFTI_GZ');
fsldir = getenv('FSLDIR');
fsldirmpath = sprintf('%s/etc/matlab',fsldir);
path(path, fsldirmpath);
clear fsldir fsldirmpath;

 % Set ITKSNAPDIR to ITK-Snap install location
setenv('ITKSNAPDIR', '/Applications/ITK-SNAP.app/Contents/bin');
itksnapdir = getenv('ITKSNAPDIR');
itksnapmpath = sprintf('%s',itksnapdir);
path(path,itksnapmpath)
clear itksnapdir itksnapmpath;
```

--------------------------------

### Run Module 3 via Python

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%203.rst.txt

Execute Module 3 using the Python script after activating the conda environment. Specify the BIDS directory and other required parameters.

```console
$ conda activate ieeg_recon
$ cd python
$ python ieeg_recon.py -s sub-RID0922 -m 3 -cs ses-clinical101 -rs ses-clinical01 -d absolute/path/to/exampleData -r -apn -mni
```

--------------------------------

### Run Module 3 using Docker

Source: https://ieeg-recon.readthedocs.io/en/latest/module%203.html

Execute Module 3 via Docker, specifying subject ID, module, sessions, data directory, radius, and segmentation options.

```bash
$ docker run -v absolute/path/to/exampleData:/source_data lucasalf11/ieeg_recon -s sub-RID0922 -m 3 -cs ses-clinical101 -rs ses-clinical01 -d /source_data -r 2 -apn

| Arguments:
| -s: subject ID
| -m: Module number
| -cs: name of session with CT scan
| -rs: name of session with reference MRI scan
| -d: path to BIDS directory
| -r: radius
| -apn: run AntsPyNet DKT and Atropos segmentation


```

--------------------------------

### Create Conda Environment for iEEG-recon

Source: https://ieeg-recon.readthedocs.io/en/latest/Getting%20Started.html

Set up a Conda environment for iEEG-recon by creating it from the provided YAML configuration file. This is necessary for running the application from the command line.

```bash
cd python
conda env create -f ieeg_recon_config.yml
```

--------------------------------

### Run Module 3 using Python (conda)

Source: https://ieeg-recon.readthedocs.io/en/latest/module%203.html

Execute Module 3 from the command line using a Python script after activating the 'ieeg_recon' conda environment. Specify subject, module, sessions, data directory, radius, and segmentation.

```bash
$ conda activate ieeg_recon
$ cd python
$ python ieeg_recon.py -s sub-RID0922 -m 3 -cs ses-clinical01 -rs ses-clinical01 -d ../exampleData -r 2 -apn

| Arguments:
| -s: subject ID
| -m: Module number
| -cs: name of session with CT scan
| -rs: name of session with reference MRI scan
| -d: path to BIDS directory
| -r: radius (in mm) of the electrode spheres used to assign regions to each electrode
| -apn: run AntsPyNet DKT and Atropos segmentation


```

--------------------------------

### Run Module 3 with Conda and MNI Registration

Source: https://ieeg-recon.readthedocs.io/en/latest/module%203.html

Execute Module 3 using Conda environment, specifying subject ID, module number, session details, BIDS directory, radius, AntsPyNet atlas, and MNI registration.

```bash
$ conda activate ieeg_recon
$ cd python
$ python ieeg_recon.py -s sub-RID0922 -m 3 -cs ses-clinical101 -rs ses-clinical01 -d absolute/path/to/exampleData -r -apn -mni

| Arguments:
| -s: subject ID
| -m: Module number
| -cs: name of session with CT scan
| -rs: name of session with reference MRI scan
| -d: path to BIDS directory
| -r: radius
| -apn: use atropos atlas from AntsPyNet
| -mni: (optional) perform MNI registration

```

--------------------------------

### Run Module 3 via MATLAB

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%203.rst.txt

Set up subject and session variables in MATLAB and then call the 'module3' method on the subject object to run Module 3. This uses the default AntSpyNet atlas.

```matlab
% Set up
subID = 'sub-RID0922';          % subject ID
ct_session = 'ses-clinical01';  % name of session with CT scan
mri_session = 'ses-clinical01'; % name of session with reference MRI scan
BIDS_dir = '../exampleData';    % path to BIDS directory

subject_rid922 = ieeg_recon(subID, ct_session, mri_session, BIDS_dir);

% Run Module 3
fileLocations = subject_rid922.module3;
```

--------------------------------

### Run Module 3 via Python

Source: https://ieeg-recon.readthedocs.io/en/latest/_sources/module%203.rst.txt

Execute Module 3 from the command line using a Python script after activating the 'ieeg_recon' conda environment. This command uses the default AntSpyNet atlas.

```console
conda activate ieeg_recon
cd python
python ieeg_recon.py -s sub-RID0922 -m 3 -cs ses-clinical01 -rs ses-clinical01 -d ../exampleData -r 2 -apn
```
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