Instructors:
- Matt McCormick, PhD, Kitware, Inc
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 or JavaScript and making ITK available via leading applications such as Slicer, ImageJ, and Napari. Moreover, the toolkit has transformed into a accessible foundation for advanced, progressive bioimaging web applications. In this course, we present best practices for taking advantage of ITK in your imaging research and commercial products. We demonstrate how to utilize the algorithms in ITK, including the multitude of ITK extensions that are freely available on the web, and how to leverage with the broader open source technological ecosystem for scientific image analysis, visualization, and artificial intelligence.
For most of the tutorials sections, simply install the Python dependencies in the requirements.txt file.
The following instruction provide a complete setup that supports native C++ development, WebAssembly development, and Python scripting.
We will be using the bash
shell. On Windows this is available with the standard Git installation as Git Bash. Bash is installed by default on macOS and Linux.
If you do not have a python environment manager available, we recommend micromamba.
"${SHELL}" <(curl -L micro.mamba.pm/install.sh)
Create an environment with Python 3.11, activate it, and install the course Python dependencies.
micromamba create -n itk-course "python=3.11" -c conda-forge
Activate the environment and install required Python packages:
micromamba activate itk-course
python -m pip install -r requirements.txt
python -m bash_kernel.install
Install the standard C++ compiler for your operating system, GCC on Linux, AppleClang on macOS, and Visual Studio on Windows.
Install CMake
Install pnpm, the fast, efficient package-manager for JavaScript development.
curl -fsSL https://get.pnpm.io/install.sh | sh -
If Node.js has not already been installed, it can be installed with pnpm:
pnpm env use --global lts
Install the Wasmtime CLI:
curl https://wasmtime.dev/install.sh -sSf | bash
- On Linux, make sure you can run
docker
withoutsudo
. - On Windows, we recommend WSL 2 with Docker enabled. Note that this also avoids licensing issues related to Docker Desktop.
Run the check-your-environment notebook:
jupyter lab ./check_env.ipynb