We present a new version of STIR (Software for Tomographic Image Reconstruction), an open source object-oriented library implemented in C++ for 3D positron emission tomography reconstruction. This library has been designed such that it can be used for many algorithms and scanner geometries, while being portable to various computing platforms. This second release enhances its flexibility and modular design and includes additional features such as Compton scatter simulation, an additional iterative reconstruction algorithm and parametric image reconstruction (both indirect and direct). We discuss the new features in this release and present example results. STIR can be downloaded from http://stir.sourceforge.net.

We present a new version of STIR, an Open Source object-oriented library implemented in C++ for 3D PET reconstruction. This library has been designed such that it can be used for many algorithms and scanner geometries, while being portable to various computing platforms. This second release enhances its flexibility and modular design and includes additional features such as Compton scatter simulation, an additional iterative reconstruction algorithm and parametric image reconstruction (both indirect and direct). We discuss the new features in this release and present example results. STIR can be downloaded from http://stir.sourceforge.net.

We discuss a motion correction scheme for rigid body motion in PET if the movement is known. Several groups have previously proposed a 2 stage process for motion correction: acquiring the data in list-mode and realigning the events according to the known motion before binning them into a sinogram, followed by reconstruction of the sinogram. However, motion correction of the sinogram data can result in parts of the sinogram not being filled for the full duration of the time frame. This results in image artefacts. We suggest ways to remove these artefacts by either reprojecting data or by determining scale factors for the partially measured parts of the sinogram, or a combination of both. We test this on simulations, phantom data and one patient study.

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In this work the level of positive bias in images generated by various iterative reconstructions of low activity PET data was investigated. A 3D acquisition of a low activity cylinder was performed upon an EXACT3D PET scanner followed by a multi-trial single plane simulation based upon this scan, taking into account randoms, scatter and attenuation. These were reconstructed using different implementations of Maximum Likelihood Expectation Maximisation, including the simple case of fully precorrected data and also using a separate randoms estimate with the Shifted Poisson and Prompts approaches. The effect of estimating the mean of randoms from the noisy delayed randoms with a Maximum Likelihood technique was also investigated.0-7803-7636-6/03/$17.00 ©2003 IEEE. 0-7803-7636-6/03/$17.00 ©2003 IEEE.