PyTomography

A Python Library for Quantitative Medical Image Reconstruction

PyTomography is an open-source, GPU-accelerated python library providing both extensive system modeling for SPECT/PET systems as well as associated reconstruction algorithms for quantitative imaging. PyTomography uses the functionality of PyTorch to (i) enable fast GPU-accelerated reconstruction and (ii) permit easy integration of deep-learning models in traditional reconstruction algorithms. It aims at creating a central platform for the development, validation, and deployment of novel tomographic reconstruction algorithms. For those familiar with python programming, it is simple to install and use, and there are a variety of tutorials available to assist in learning the software. This work is licensed under an MIT license.

Features

Supported Modalities

Single Photon Computed Emission Tomography (SPECT)
- System matrix modeling includes attenuation correction, PSF modeling, scatter correction
2D Positron Emission Tomography (PET)
- System matrix modeling includes attenuation correction and radially dependent PSF modeling.

Reconstruction Algorithms

Filtered Back Projection (FBP)
Statistical Iterative Algorithms
- OSEM / MLEM
- OSEMOSL
- BSREM
- KEM

Options exist to include anatomical information (such as MRI/CT) when using priors/regularization.

Supported Datatypes

DICOM
- Ability to open and align SPECT/CT data and create attenuation maps
- Repository of collimator parameters for different scanners for obtaining PSF information
SIMIND output files (interfile)
- Functionality to combine multiple sets of projections (representing different organs/regions) into a single set of projection data

Note: If you use PyTomography in your own research, please cite its Reference Publication