• Here you will find all the implementation necessary to reproduce the paper.
• For an illustrative notebook link
• The research paper is available at link

This repository is part of the IA369Z project course from School of Electrical and Computer Engineering (FEEC) at the University of Campinas. The algorithms contained here are part of the study of the paper "Corpus callosum diffusion properties differences in systemic lupus patients" and describe the ROQS segmentation method, the Witelson and Hofer and Frahm's parcellation methods. As well as the statistical analysis of the diffusion properties of the subjects.

Do not freak out! It is easier than you think. Let's get started:

• Python 2.7.13
• Numpy 1.12.1
• Nibabel 2.1.0
• Matplotlib 2.0.0
• External libraries: ia870, dtimp, functions_will and ia636, also available here

There are two different manners to reproduce this paper using Jupyter Notebook:

• through Anaconda (locally)
• through Docker image

• Install Anaconda 4.3.1 for Python 2.7.13, it does not work for Python 3.x : Windows, Mac or Linux

• To install the neuroimaging package, open up a terminal and type the following command: pip install nibabel. For more information link

• Go ahead and clone this repository typing the following command in your terminal: git clone https://github.com/mariecpereira/IA369Z

• In the same terminal, type: jupyter notebook

• In your browser, paste the URL, the IPython Notebook is running at: http://0.0.0.0:8888/

• Follow the instructions and access the files into the deliver folder to reproduce the paper

• Install Docker link

• Go ahead and clone this repository typing the following command in your terminal: git clone https://github.com/mariecpereira/IA369Z

• Open the terminal in your computer and enter the command to run the image and to create the container: sudo docker run -p 8888:8888 -v <the path you cloned IA369Z repository>:/home/ds/notebooks mecp/ia369z

• In your browser, paste the URL, the IPython Notebook is running at: http://0.0.0.0:8888/

• Follow the instructions and access the files into the deliver folder to reproduce the paper

• Install Docker link

• Go ahead and clone this repository typing the following command in your terminal: git clone https://github.com/mariecpereira/IA369Z

• Open the terminal in your computer and enter the command to run the image and to create the container: sudo docker run -d -p 8888:8888 -v <the path you cloned IA369Z repository>:/home/ds/notebooks mecp/ia369z

• In your browser, paste the URL, the IPython Notebook is running at: http://0.0.0.0:8888/

• Follow the instructions and access the files into the deliver folder to reproduce the paper

• Install Docker, for Windows 10 Professional and Enterprise 64-bits link OR Install Docker Toolbox for other Windows versions link

• Go ahead and clone this repository typing the following command in your terminal, cloned directory must be inside C:\Users{user} directory: git clone https://github.com/mariecpereira/IA369Z

• Open the terminal in your computer and enter the command to run the image and to create the container: docker run -p 8888:8888 -v <the path you cloned IA369Z repository>:/home/ds/notebooks mecp/ia369z

• In your browser, paste the URL, you must copy and paste your IP address, and so the IPython Notebook is running at: http://<your IP address>:8888

• Follow the instructions and access the files into the deliver folder to reproduce the paper

If you are going to run the code locally, make sure you had already downloaded the external libraries listed above and pasted them into the same folder you cloned the IA369Z repository. If you chose to run the code through Docker image do not worry about it!

For a data sample email: mariecpereira@gmail.com

Please make sure your data sample's name matches the data path into the code.

Once you got all the requirements listed above set up, all you need to do is to run and test the code/data. Make sure that everything is at the same local folder.

For questions or more details email: mariecpereira@gmail.com