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Copyright (c) 2019 OERCompBiomed

Setting up your system


We recommend installing Python via the Anaconda Distribution. Be sure to use the "Python 3.6.x" version or later. We will use the Conda Package Management System within the Anaconda Distribution. From the documentation:

Conda is an open source package management system and environment management system that runs on Windows, macOS and Linux. Conda quickly installs, runs and updates packages and their dependencies. Conda easily creates, saves, loads and switches between environments on your local computer.

After the installation run python --version in a terminal window (in "Anaconda Prompt" if you are using Windows). If the output show "Python 3.6.x" or later (and "Anaconda") you are good to go.


Atom is a free and open-source text and source code editor for writing and editing text files e.g. YAML configuration files, Markdown files, JSON files, HTML files and others. By its developers it is called a "hackable text editor for the 21st Century" and is a useful tool in addition to the browser-based Jupyter notebook that we will use. Install Atom (Mac Windows Linux) from:


ITK-SNAP is an open-source image analysis tool used to segment and label structures in 3D medical images. ITK-SNAP is supported on Mac, Windows and Linux and provides semi-automatic segmentation using active contour methods, as well as manual delineation and image navigation. You can read and interact with DICOM and NIFTI images, and plot time-course data. Download the newest release of ITK-SNAP at


The course code is hosted on the code-sharing platform GitHub (where you now are reading this). If you do not have a GitHub account already you should make one now. We recommend that you are using the platform for your own projects during the course.

Install and test the course environment:

After you have successfully installed Anaconda, go through the following steps (if you are using Windows, be at the "Anaconda Prompt").

Install Git:

conda install git

Download the repository:

git clone
cd Seili-2019

Configure the Python-environment:

conda env update

Activate the environment:

conda activate Seili

If you are using Linux or MacOS and the command above fails, type

source ~/.bash_profile

and try conda activate Seili again. If this fails, activate the environment by typing source activate Seili instead.

Install a Jupyter kernel:

python -m ipykernel install --user --name Seili --display-name "SEILI"

Install notebook extensions ipywidgets:

jupyter nbextension enable --py --sys-prefix widgetsnbextension

Optionally install Jupyter extensions:

These are useful to have nice tables of contents in the notebooks, but they are not required.

conda install -n Seili -c conda-forge jupyter_contrib_nbextensions

Test you installation:

Go through the notebook 0.0-test.ipynb in the notebooks-directory:

cd notebooks
jupyter notebook

You can also use JupyterLab: jupyter lab.


The code and environment will be updated during the course. Run the following commands regularly:

  • Update code: git pull
  • Update environment:
conda activate Seili
conda env update

Note on Notebooks:

The course is based on the Jupyter Notebook, a web-based framework for developing and presenting code-based projects (take a look at og for introductions to Jupyter Notebooks).

Throughout the course you will work with notebooks that contain various material and programming tasks. We recommend that you make a copy of our notebooks before you are editing them. For your own version of the notebook you might adopt the naming convention my_[name_of_notebook].ipynb. When running your notebook, remember to change the kernel to SEILI.

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