EMRECON: An expectation maximization based image reconstruction framework for emission tomography data

Abstract

We present a flexible image reconstruction framework for emission tomography data called EMRECON. The software includes multiple expectation maximization based reconstruction algorithms as well as support for several scanner geometries. In order to implement novel reconstruction techniques (e.g. TV-based regularization or combined reconstruction and motion correction) or scanner models, full access to every stage of the reconstruction pipeline is vital. EMrecon is fully open and well-documented, thus permits testing without the need to care about data formats or standard reconstruction and data correction algorithms. Due to the GATE-like syntax new scanner geometries, including an exact definition of each single crystal, can be added easily. The parallel (multi-core) C implementation was successfully tested on several Linux distributions. This makes EMRECON a useful tool for the development of new reconstruction algorithms and also serves as a platform for testing different scanner geometries.