We present an enhancement of the OSEM (ordered set expectation maximization) algorithm for 3D PET reconstruction, which we call the inter-update Metz filtered OSEM (IMF-OSEM). The IMF-OSEM algorithm incorporates filtering action into the image updating process in order to improve the quality of the reconstruction. With this technique, the multiplicative correction image--ordinarily used to update image estimates in plain OSEM--is applied to a Metz-filtered version of the image estimate at certain intervals. In addition, we present a software implementation that employs several high-speed features to accelerate reconstruction. These features include, firstly, forward and back projection functions which make full use of symmetry as well as a fast incremental computation technique. Secondly, the software has the capability of running in parallel mode on several processors. The parallelization approach employed yields a significant speed-up, which is nearly independent of the amount of data. Together, these features lead to reasonable reconstruction times even when using large image arrays and non-axially compressed projection data. The performance of IMF-OSEM was tested on phantom data acquired on the GE Advance scanner. Our results demonstrate that an appropriate choice of Metz filter parameters can improve the contrast-noise balance of certain regions of interest relative to both plain and post-filtered OSEM, and to the GE commercial reprojection algorithm software.

In this paper a clustering technique is proposed for attenuation correction (AC) in positron emission tomography (PET). The method is unsupervised and adaptive with respect to counting statistics in the transmission (TR) images. The technique allows the classification of pre- or post-injection TR images into main tissue components in terms of attenuation coefficients. The classified TR images are then forward projected to generate new TR sinograms to be used for AC in the reconstruction of the corresponding emission (EM) data. The technique has been tested on phantoms and clinical data of brain, heart and whole-body PET studies. The method allows: (a) reduction of noise propagation from TR into EM images, (b) reduction of TR scanning to a few minutes (3 min) with maintenance of the quantitative accuracy (within 6%) of longer acquisition scans (15-20 min), (c) reduction of the radiation dose to the patient, (d) performance of quantitative whole-body studies.

Summary. We present a object-oriented library of C++ features for 3D PET reconstruction. This library has been designed so that it can be used for many algorithms and scanner geometries. Its flexibility, portability and modular design have helped greatly to (a) develop new iterative algorithms, (b) compare iterative and analytic methods using simulated, phantom and patient data, (c) adapt and apply the developed reconstruction algorithms to different designs of tomographs. As 3D iterative reconstruction algorithms are time consuming, the library contains classes and functions to run parts of the reconstruction in parallel, using parallel platforms with a distributed memory architecture.

A physical model has been developed in order to study the forces induced on the tire by road irregularities. It works in a range of frequencies 0–250 Hz, i.e. up to frequencies that are felt by the passengers as noise and vibrations, but it can be easily improved to 400 Hz. The model can resolve road irregularities with wavelength greater than 5 cm (pavement megatexture). The parameters of this model have been identified by comparison with special virtual tests performed on a 3D finite element model of the tire, i.e. without using any experimental data. Once built, the model can be used to analyze the forces transmitted by the tire to the vehicle while passing over various pavement textures for testing both the tire-vehicle system and the pavement textures. Since the model doesn't require any experimental data, it can be used to predict the dynamical characteristics of tires which haven't been built yet, speeding up the optimization process of tires under development. Due to its characteristics, this model appears to be a powerful tool for a joint analysis of vehicle and tire, but it would require vehicle models with a similar frequency response range, currently not reported in literature. Comparisons with the results of indoor cleat tests and with measurements on a test car with an instrumented wheel hub have shown that the mathematical model reproduces with good accuracy the behavior of the tire in the frequency range of interest.