Getting Started¶
Welcome to SimpleITK!
SimpleITK provides a simplified interface to ITK in a variety of languages. You can either download binaries, if they are available for your platform and preferred language, or you can build SimpleITK yourself from the source code.
In the following sections we describe how to install SimpleITK and additional auxiliary programs you will find useful.
After you have installed SimpleITK, we recommend going over the latest tutorial and skimming the Doxygen pages for more information.
Downloading the binaries¶
One of the great advantages of SimpleITK is that (typically) you do not have to build it — you can simply download the binaries and get started right away!
Currently, Python binaries are available on Microsoft Windows, GNU Linux and Apple OS X. C# and Java binaries are available for Windows. We are also working towards supporting R packaging.
Python binary files¶
There are currently two Python binary package choices: Python Wheels, and Anaconda packages for the Anaconda Python distribution. We recommend the use of a virtual environment for installation of SimpleITK.
Wheels for Generic Python Distribution¶
From the command line use the pip program to install a binary wheel:
pip install SimpleITK
This installation requires a recent version of pip (>=9.0), to properly detect
compatibility with the PEP 427 tags in the wheel
filenames. You can update your version of pip using pip install -U pip
.
Also your Python environment must be compatible with one of
the pre-compiled binary wheels.
Alternatively, the wheels can be manually downloaded from GitHub releases or PyPI, and then installed with pip.
Conda-based distributions (Anaconda, Miniconda)¶
From the command line prompt, execute:
conda install -c simpleitk simpleitk
Beta and release candidate packages are also available on Anaconda cloud under the dev label:
conda install -c simpleitk/label/dev simpleitk
C# binary files¶
Binaries for select C# platforms can be found on SimpleITK’s GitHub releases under the appropriate version. Installing the library should only involve importing the unzipped files into you C# environment. The files have the following naming convention:
SimpleITK-version-CSharp-buildplatform-targetplatform.zip
e.g.
SimpleITK-1.2.0-CSharp-win64-x64.zip
Details about how to set up a C# Visual Studio project with SimpleITK can be found in the setup SimpleITK with CSharp.
Java binary files¶
Binaries for select Java platforms can be found on SimpleITK’s GitHub releases page under the appropriate version. Installation instructions are available at setup SimpleITK with Java.
R binary files¶
Only available for Linux and Mac.
Install using a devtools based installer (GitHub Repository). Strictly speaking, this is not a binary distribution, but this is a convenient way of automatically compiling and installing on your system.
Requires R devtools, CMake, git and a compiler in the path.
From the R prompt:
devtools::install_github("SimpleITK/SimpleITKRInstaller")
Latest binaries¶
If the latest SimpleITK bug fixes or features are required then pre-release binaries are needed. The pre-release binaries are built from the actively developed master branch. The SimpleITK packages are available on Github releases under the “latest” tag. The packages include Python, CSharp and Java. To upgrade to the latest pre-release Python binary package run:
pip install --upgrade --pre SimpleITK --find-links https://github.com/SimpleITK/SimpleITK/releases/tag/latest
Recommended Software¶
Fiji (Fiji is Just ImageJ)¶
SimpleITK has a built in function itk::simple::Show() which can be used for viewing images in an interactive session. By default this Show function searches for an installed Fiji to display images. If Fiji is not found, then it searches for ImageJ. Fiji/ImageJ were chosen because they can handle all the image types that SimpleITK supports, including 3D vector images with n components.
The Show function first searches the “PATH” environment variable, then additional standard locations are examined, if problems are encountered the correct path can be added to this environment variable and the “debugOn” option to “Show” flag set.
The Show function can also be configured to invoke some other viewing application using the SITK_SHOW_COMMAND environment variable.
IPython and Jupyter¶
If you are using python, IPython with Jupyter is terrific environment to perform interactive computing for image processing. With the addition of numpy and scipy, you will have a powerful interactive environment.
We have instructional SimpleITK Jupyter Notebooks which can help you get started.