Frequently Asked Questions

This page hosts frequently asked questions about SimpleITK, and their answers.

Installation

I am using the binary distribution of SimpleITK for Anaconda, why do I get an error about libpng?

ImportError: dlopen(./_SimpleITK.so, 2): Library not loaded: @rpath/libpng15.15.dylib   Referenced from: …/lib/python2.7/site-packages/SimpleITK/_SimpleITK.so   Reason: image not found

This type of error can occour if a library SimpleITK depends on can not be found. It may be that the version of the dependent library has changed in the Python environment and is no longer compatible. One solution is to create a environment.yml file with all the packages required for your project, then create a new environment:

conda env create -f environment.yml

How to Use

What filters are currently available in SimpleITK?

There are nearly 300 ITK image filters wrapped in SimpleITK. We have a list of filters accompanied by a brief description. Additionally the Doxygen can be examined to determine the availability of a filter.

What image file formats can SimpleITK read?

See here.

How do I read a RAW image into SimpleITK?

In general raw image files are missing information. They do not contain the nessesary header information to describe the basic size and type for the data, so this format is intrinsically deficient. The RawImageIO class is not available in SimpleITK so there is no direct way to programmatically hard code this header information. The suggested way is to create a Meta image header file (*.mhd) which references the raw data file and describes the size and type of the data. The documentation on how to write a Meta image header can be found here.

The following is a sample Meta image header file, perhaps of name sample.mhd:

ObjectType = Image
NDims = 3
DimSize = 256 256 64
ElementType = MET_USHORT
ElementDataFile = image.raw    (this tag must be last in a MetaImageHeader)

Why isn’t ImageJ found by the Show function (RuntimeError: Exception thrown…)?

The SimpleITK Show function expects the ImageJ program to be installed in specific locations. The recommended installation locations are:

  • On Windows: in your user directory (e.g. C:\Users\your_user_name\Fiji.app).
  • On Linux: in ~/bin .
  • On Mac: in /Applications .

To see the locations where the function is searching set its debugOn flag.

In Python:

sitk.Show(image, debugOn=True)

In R:

Show(image, "file_name", TRUE)

You can also indicate where a viewer (not necessarily ImageJ) is found by setting the path to the viewer in an environment variable SITK_SHOW_COMMAND.

Can I use another image file viewer beside ImageJ?

By default when the Show function is called, SimpleITK writes out a temporary image in Nifti format then launches ImageJ. The user can override the file format of the temporary file and/or the application used to handle that file.

The temporary file format can be specified via the SITK_SHOW_EXTENSION environment variable. For example, if the user wanted to export a PNG file, on Linux it might look like this:

SITK_SHOW_EXTENSION=".png"
export SITK_SHOW_EXTENSION

Use of an extension unsupported by ITK results in an error message. For the supported image formats, here is the ITK Image IO Filters.

The default display application for all image types is ImageJ. To override ImageJ with some other application, use the SITK_SHOW_COMMAND environment variable. For instance, on Unix systems, using GNOME’s image viewer eog would be:

SITK_SHOW_EXTENSION=".png"
export SITK_SHOW_EXTENSION
SITK_SHOW_COMMAND="eog"
export SITK_SHOW_COMMAND

To override the default display applications for only color or 3d images, there are the SITK_SHOW_COLOR_COMMAND and SITK_SHOW_3D_COMMAND environment variables.

More details on the Show function, including use of the “%a” and “%f” tokens, is at the Show function Doxygen page.

How can I use 3D Slicer to view my images?

3D Slicer is a very powerful and popular application for visualization and medical image computing. The SITK_SHOW_COMMAND environment variable may be used to display images in Slicer instead of SimpleITK’s default viewer, ImageJ. The following are examples of what settings for SITK_SHOW_COMMAND might look like for Mac OS X, Linux and Windows to use Slicer.

Mac OS X

export SITK_SHOW_COMMAND=/Applications/Slicer.app/Contents/MacOS/Slicer

Linux

export SITK_SHOW_COMMAND=Slicer

Windows

set SITK_SHOW_COMMAND=:"c:\Program Files\Slicer 4.2.2-1\Slicer"

The value of SITK_SHOW_COMMAND should be modified to point to wherever Slicer is installed. If you only want to use Slicer for volumetric 3D images, use the SITK_SHOW_3D_COMMAND environment variable instead of SITK_SHOW_COMMAND.

How can I use a newer Java with ImageJ on Mac OS X?

By default on Mac OS X, the ImageJ application expects Java 6, which is old and unsupported. The latest supported version of Java (currently version 8u25) can be downloaded from Oracle’s Java Development kit page. The following bash commands will set up the SITK_SHOW_COMMAND and SITK_SHOW_COLOR_COMMAND to invoke ImageJ’s jar file using the Java compiler.

ij="/Applications/ImageJ/"
ijcmd="java -Dplugins.dir=$ij/plugins -jar $ij/ImageJ.app/Contents/Resources/Java/ij.jar"
export SITK_SHOW_COMMAND="$ijcmd -eval 'open( \"%f\" );'"
export SITK_SHOW_COLOR_COMMAND="$ijcmd -eval 'open( \"%f\" ); run(\"Make Composite\", \"display=Composite\");'"

The first lines set a variable pointing to the standard location for the ImageJ directory. If ImageJ is installed somewhere else, the line should be modified. The second line provides the command to launch ImageJ using the Java compiler. It includes flags that point to ImageJ’s plugiin directory and ImageJ’s ij.jar file.

The SITK_SHOW_COMMAND tells SimpleITK.Show() to launch Java with ij.jar and then execute the open macro with an image file. The SITK_SHOW_COLOR_COMMAND does these same things and then executes the ImageJ “Make Composite” command to treat a multichannel image as a composite color image.

Wrapping

Python

Why should I use a virtual environment?

Before you install SimpleITK we highly recommend that you create a virtual environment into which you install the package. Note that different Python versions and distributions have different programs for creating and managing virtual environments.

The use of a virtual environment allows you to elegantly deal with package compatability issues, to quote The Hitchhiker’s Guide to Python!:

A Virtual Environment is a tool to keep the dependencies required by different projects in separate places, by creating virtual Python environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable.

Programs for creating virtual environments include virtualenv and pyvenv for generic Python distributions, conda for the anaconda distribution, and canopy_cli for the canopy distribution.

Are the Python Wheels compatible with Enthought Canopy Distribution?

The Generic Python Wheels frequently seem to work with the Enthought Canopy Python distribution. However, it is recommended that you compile SimpleITK explicitly against this Python distribution to ensure compatibility.

Tcl

Java

C#

R

Compilation

Is my compiler supported?

SimpleITK uses advanced C++ meta-programming to instantiate ITK’s Images and Filters. Addtionally, we use some headers which are included in the C99 and C++ TR1 extension. Therefore SimpleITK places additional requirements on the compiler beyond what is required for ITK. In principle we require C++x03 with C99’s “stdint.h” and TR1’s “functional”. If your compiler has those features it is likely able to be supported.

The additional requirement for a supported compiler is that it is on the nightly dashboard. With this regard, the list of supported compilers is on the SimpleITK SimpleITK dashboard. We welcome user contributions to the nightly dashboard to expand the list of supported compilers.

Noted Problems

  • Microsoft compilers before Visual Studio 14 (2015) have had memory limitation issues.

Why am I getting a compilation error on OSX?

With SimpleITK <=0.7 the following error occurred during compilation on Apple OSX 10.9 Mavericks with clang 5.0:

SimpleITK/Code/Common/include/sitkMemberFunctionFactoryBase.h:106:16:  error: no member named 'tr1' in namespace 'std'
typedef std::tr1::function< MemberFunctionResultType ( ) > FunctionObjectType;
~~~~~^

With Xcode 5.0, Apple’s distributed version of clang (5.0) changed which implementation of the C++ Standard Library it uses by default. Previous versions of clang (4.2 and earlier) used GNU’s libstdc++ , while clang 5.0 now uses LLVM’s libc++. SimpleITK 0.7 and earlier require certain features from C++ tr1 which are not implemented in LLVM’s libc++ but are available in GNU’s libstdc++.

To build SimpleITK <=0.7 with clang 5.0, you can configure the compiler to use GNU’s stdlibc++. This change must be done at the initial configuration:

cmake "-DCMAKE_CXX_FLAGS:STRING=-stdlib=libstdc++" ../SimpleITK/SuperBuild

NOTE: If you already have a build directory which has been partially configured the contents must be deleted. The above line needs to be done for an initial configuration in an empty build directory. NOTE: This work around does not work when with the CMake “Xcode” generator. It is recommended to just use the default “Unix Makefiles” generator, to build SimpleITK, and get using SimpleITK, not building it.

The following is a compatibility table for clang 5.0. It shows that the default of libc++ does not work with SimpleITK, while the other options do. The choice of which standard library to use and which C++ language standard to use are independent.

Clang 5.0 compatibility -stdlib=libc++ -stdlib=libstdc++
(c++03) FAIL OK
-std=c++11 OK (>=0.8) OK

For SimpleITK >=0.8, support for the tr1 features migrated to C++11 has been improved with better feature detection, and the necessary flags are now automatically added. LLVM’s libc++ will now work if compiling with the C++11 standard by adding the flag “-std=c++11” in the initial configuration.

To further complicate dependencies and interactions, some downloadable languages such as Java, or R, may be compiled against GNU’s libstdc++. This may cause a conflict in the types used in the interface resulting in compilation errors while wrapping the language.

Why does the Superbuild fail compiling PCRE on Mac OS X?

If the Xcode command line tools are not properly set up on OS X, PCRE could fail to build in the Superbuild process with messages such as:

checking whether we are cross compiling... configure: error: in `/your/build/path/SimpleITK/PCRE-prefix/src/PCRE-build':
configure: error: cannot run C compiled programs.
If you meant to cross compile, use `--host'.
See `config.log' for more details
[10/13] Performing build step for 'PCRE'

To install the command line developer tools enter the following:

xcode-select --install

To reset the default command line tools path:

xcode-select --reset

Do I need to download an option package for TR1 support?

Visual Studio 2008 requires an additional download for TR1 support. This support is best provided with the Service Pack 1. There is a separate TR1 feature pack which can be downloaded, but it is no longer recommended since Service Pack 1 includes TR1 and numerous bug and performance improvements.

What Configurations on Windows are Supported For Building?

We recommend to use Microsoft Visual Studio 14 (2015) or newer to compile SimpleITK.

Where is the Test Data?

The testing data is not stored in the SimpleITK repository or as part of the source code. It is mirrored on several data repositories on the web.

If you have obtained the source code from the git repository, it should be downloaded as part of the build process via the CMake ExternalData module.

You can download a tar-ball of the “SimpleITKData” for a release from the GitHub Assets, which contains the external data. It should populate the .ExternalData subdirectory of the SimpleITK source code directory when extracted.

Why is CMake unable to download ExternalData?

When compiling SimpleITK you may get and error like the following:

Object MD5=2e115fe26e435e33b0d5c022e4490567 not found at:
 https://placid.nlm.nih.gov/api/rest?method=midas.bitstream.download&checksum=2e115fe26e435e33b0d5c022e4490567&algorithm=MD5 ("Unsupported protocol")
 https://simpleitk.github.io/SimpleITKExternalData/MD5/2e115fe26e435e33b0d5c022e4490567 ("Unsupported protocol")
 https://midas3.kitware.com/midas/api/rest?method=midas.bitstream.download&checksum=2e115fe26e435e33b0d5c022e4490567&algorithm=MD5 ("Unsupported protocol")
 https://insightsoftwareconsortium.github.io/ITKTestingData/MD5/2e115fe26e435e33b0d5c022e4490567 ("Unsupported protocol")
 https://itk.org/files/ExternalData/MD5/2e115fe26e435e33b0d5c022e4490567 ("Unsupported protocol")

This indicates that CMake was not compiles with SSL support. The “Unsupported protocol” message indicate that CMake can not communicate via “https”.

The solution is to use a compiled version of CMake which supports SSL. If you compile CMake yourself, simply reconfigure CMake with the “CMAKE_USE_OPENSSL” option enabled.