Occiput - Tomographic Vision
Tomographic reconstruction software for PET, PET-MRI and SPECT in 2D, 3D (volumetric) and 4D (spatio-temporal) in Python.
The software provides high-speed reconstruction using Graphics Processing Units (GPU). Note: an NVidia CUDA-compatible GPU is required.
Occiput can be utilized with arbitrary scanner geometries. It can be utilized for abstract tomographic
reconstruction experiments to develop new algorithms and explore new system geometries, or to connect to real-world scanners,
providing production quality image reconstruction with standard algorithms (such as MLEM and OSEM).
Occiput implements advanced algorithms for motion correction, kinetic imaging, multi-modal reconstruction, respiratory and cardiac gated imaging.
The source code contains Jupyter notebooks with examples.
A Python extension package
Occiput_Interface_Biograph_mMR, implementing the interface to the Siemens Biograph mMR PET-MRI scanner
is available upon request and following authorization from Siemens. Notebooks containing Biograph_mMR in the title can
only be executed after installing the extension package.
Please email us at email@example.com
Linux, Windows (not tested recently), MacOS
Pre-requisites: Occiput requires
NVidia GPU Drivers,
NVidia CUDA and the
NiftyRec GPU accelerated tomographic ray-tracing library.
- Install NVidia GPU Drivers and CUDA
- Install NiftyRec libraries - build the latest version using CMake
- Make sure that CUDA libraries and NiftyRec libraries are in the system path:
setx path "%path%;c:/path_to_cuda_libraries:/path_to_niftyrec_libraries;"
git clone https://github.com/spedemon/occiput.git
python setup.py build install
Examples and demos of the features of Occiput are in the /occiput/notebooks folder.
To get started, install
Python Jupyter and open the scripts in
notebook /occiput/notebooks/DOCUMENTATION.ipynb contains
an index and short description of the notebooks.
For more information see occiput.io.