Biomedical Image Analysis and Visualization: ITK

Kitware, Carrboro, North Carolina, USA

Instructors:

• Matt McCormick, PhD
• Dženan Zukić, PhD
• Francois Budin

The Insight Toolkit (ITK) (www.itk.org) has become a standard in academia and industry for medical image analysis. In recent years, the ITK community has focused on providing programming interfaces to ITK from Python and JavaScript and making ITK available via leading applications such as Slicer and ImageJ. In this course we present best practices for taking advantage of ITK in your imaging research and commercial products. We demonstrate how script writing and can be used to access the algorithms in ITK and the multitude of ITK extensions that are freely available on the web.

Run the Tutorial

There are many ways to run these tutorials.

On the Web, with Binder

To run the notebooks in MyBinder, simply click this link.

Locally, with Python from Python.org or a System Python

First, install Python, if not already available.

Next, install the required dependencies:

python -m pip install tornado==5.1.1 jupyter matplotlib numpy scipy ipywidgets scikit-learn cookiecutter
python -m pip install --upgrade --pre itk itk-texturefeatures
python -m pip install itkwidgets

Then, clone the repository:

git clone https://github.com/KitwareMedical/2019-03-13-KRSCourseInBiomedicalImageAnalysisAndVisualization.git
cd 2019-03-13-KRSCourseInBiomedicalImageAnalysisAndVisualization

And start Jupyter:

python -m jupyter notebook

Locally, with Conda

First, install MiniConda or Anaconda, if not already available.

Next, install the required dependencies:

conda install -c conda-forge jupyter matplotlib numpy scipy ipywidgets scikit-learn cookiecutter
python -m pip install --upgrade --pre itk itk-texturefeatures
python -m pip install itkwidgets

Then, clone the repository:

git clone https://github.com/KitwareMedical/2019-03-13-KRSCourseInBiomedicalImageAnalysisAndVisualization.git
cd 2019-03-13-KRSCourseInBiomedicalImageAnalysisAndVisualization

And start Jupyter:

python -m jupyter notebook

Locally, with Docker

First, install Docker, if not already available.

Next, clone the repository:

git clone https://github.com/KitwareMedical/2019-03-13-KRSCourseInBiomedicalImageAnalysisAndVisualization.git
cd 2019-03-13-KRSCourseInBiomedicalImageAnalysisAndVisualization

Then, build and run the Docker image:

./build.sh
./run.sh

Paste the URL presented in the terminal in your web browser.

With Jupyter Lab instead of the Jupyter Notebook

To run under [Jupyter Lab](https://jupyterlab.readthedocs.io/en/stable/) instead of the Jupyter Notebook, install the jupyterlab package and [Node.js](https://nodejs.org/en/download/), e.g.:

conda install jupyterlab nodejs

Then install the required extensions:

jupyter labextension install @jupyter-widgets/jupyterlab-manager itk-jupyter-widgets

And start Jupyter with:

python -m jupyter lab

instead of:

python -m jupyter notebook