The ASTRA Toolbox is a MATLAB and Python toolbox of high-performance GPU primitives for 2D and 3D tomography.
We support 2D parallel and fan beam geometries, and 3D parallel and cone beam. All of them have highly flexible source/detector positioning.
A large number of 2D and 3D algorithms are available, including FBP, SIRT, SART, CGLS.
The basic forward and backward projection operations are GPU-accelerated, and directly callable from MATLAB and Python to enable building new algorithms.
See the MATLAB and Python code samples in samples/ and on http://www.astra-toolbox.com/ .
Add the mex and tools subdirectories to your MATLAB path, or copy the Python astra module to your Python site-packages directory. We require the Microsoft Visual Studio 2015 redistributable package. If this is not already installed on your system, it is included as vc_redist.x64.exe in the ASTRA zip file.
Requirements: conda python environment, with 64 bit Python 2.7, 3.5 or 3.6.
There are packages available for the ASTRA Toolbox in the astra-toolbox channel for the conda package manager. To use these, run the following inside a conda environment.
conda install -c astra-toolbox astra-toolbox
We also provide development packages:
conda install -c astra-toolbox/label/dev astra-toolbox
Requirements: g++, boost, CUDA (5.5 or higher), Matlab (R2012a or higher)
cd build/linux ./autogen.sh # when building a git version ./configure --with-cuda=/usr/local/cuda \ --with-matlab=/usr/local/MATLAB/R2012a \ --prefix=$HOME/astra \ --with-install-type=module make make install
Add $HOME/astra/matlab and its subdirectories (tools, mex) to your matlab path.
If you want to build the Octave interface instead of the Matlab interface, specify --enable-octave instead of --with-matlab=... . The Octave files will be installed into $HOME/astra/octave . On some Linux distributions building the Astra Octave interface will require the Octave development package to be installed (e.g., liboctave-dev on Ubuntu).
NB: Each matlab version only supports a specific range of g++ versions. Despite this, if you have a newer g++ and if you get errors related to missing GLIBCXX_3.4.xx symbols, it is often possible to work around this requirement by deleting the version of libstdc++ supplied by matlab in MATLAB_PATH/bin/glnx86 or MATLAB_PATH/bin/glnxa64 (at your own risk), or setting LD_PRELOAD=/usr/lib64/libstdc++.so.6 (or similar) when starting matlab.
Requirements: g++, boost, CUDA (5.5 or higher), Python (2.7 or 3.x)
cd build/linux ./autogen.sh # when building a git version ./configure --with-cuda=/usr/local/cuda \ --with-python \ --with-install-type=module make make install
This will install Astra into your current Python environment.
Requirements: g++, boost, CUDA (5.5 or higher)
cd build/linux ./autogen.sh # when building a git version ./configure --with-cuda=/usr/local/cuda make make install-dev
This will install the Astra library and C++ headers.
Use the Homebrew package manager to install boost, libtool, autoconf, automake.
cd build/linux ./autogen.sh CPPFLAGS="-I/usr/local/include" NVCCFLAGS="-I/usr/local/include" ./configure \ --with-cuda=/usr/local/cuda \ --with-matlab=/Applications/MATLAB_R2016b.app \ --prefix=$HOME/astra \ --with-install-type=module make make install
Requirements: Visual Studio 2015 (full or community), boost (recent), CUDA 8.0, Matlab (R2012a or higher) and/or WinPython 2.7/3.x.
Using the Visual Studio IDE:
Set the environment variable MATLAB_ROOT to your matlab install location. Copy boost headers to lib\include\boost, and boost libraries to lib\x64. Open astra_vc14.sln in Visual Studio. Select the appropriate solution configuration (typically Release_CUDA|x64). Build the solution. Install by copying AstraCuda64.dll and all .mexw64 files from bin\x64\Release_CUDA and the entire matlab/tools directory to a directory to be added to your matlab path.
Using .bat scripts in build\msvc:
Edit build_env.bat and set up the correct directories. Run build_setup.bat to automatically copy the boost headers and libraries. For matlab: Run build_matlab.bat. The .dll and .mexw64 files will be in bin\x64\Release_Cuda. For python 2.7/3.5: Run build_python27.bat or build_python35.bat. Astra will be directly installed into site-packages.
To perform a (very) basic test of your ASTRA installation in Python, you can run the following Python command.
import astra astra.test()
To test your ASTRA installation in Matlab, the equivalent command is:
If you use the ASTRA Toolbox for your research, we would appreciate it if you would refer to the following papers:
W. van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, K. J. Batenburg, and J. Sijbers, “Fast and Flexible X-ray Tomography Using the ASTRA Toolbox”, Optics Express, 24(22), 25129-25147, (2016), http://dx.doi.org/10.1364/OE.24.025129
W. van Aarle, W. J. Palenstijn, J. De Beenhouwer, T. Altantzis, S. Bals, K. J. Batenburg, and J. Sijbers, “The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography”, Ultramicroscopy, 157, 35–47, (2015), http://dx.doi.org/10.1016/j.ultramic.2015.05.002
Additionally, if you use parallel beam GPU code, we would appreciate it if you would refer to the following paper:
W. J. Palenstijn, K J. Batenburg, and J. Sijbers, "Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)", Journal of Structural Biology, vol. 176, issue 2, pp. 250-253, 2011, http://dx.doi.org/10.1016/j.jsb.2011.07.017
The ASTRA Toolbox is open source under the GPLv3 license.