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High resolution 3D PET scanners with high count rate performance, such as the quad-HIDAC, place new demands on image reconstruction algorithms due to the large quantities of high precision list-mode data which are produced. Therefore a reconstruction algorithm is required which can, in a practical time frame, reconstruct into very large image arrays (submillimetre voxels, which range over a large field of view) whilst preferably retaining the precision of the data. This work presents an algorithm which meets these demands: Regularized One-Pass List-mode EM (ROPLE). The algorithm operates directly on list-mode data, passes through the data once only, accounts for finite resolution effects in the system model and also includes regularization. The algorithm performs multiple image updates during its single pass through the list-mode data, corresponding to the number of subsets that the data have been split into. The algorithm has been assessed using list-mode data from a quad-HIDAC, and is compared to the analytic reconstruction method 3D RP.

Summary form only given. It is only natural to dream of commercial success for new technology. Unfortunately, a technological break-through is usually only a first small step on the commercial road that has many roadwork and accident black-spots and certainly no "cones-hotline". Drawing on his experience of ten years at CERN followed by fifteen years building Oxford Positron Systems, the author revisits the highway travelled in bringing his HIDAC (HIgh Density Avalanche Chamber) technology to market for digital radiography and positron emission tomography. Particular reference is made to the personal experiences involved in transferring technology from multinational laboratory to small entrepreneurial company.

We report on the development of a spectrometer for muon spin rotation based on multiwire proportional chambers. The coordinates provided by telescopes each composed of two chambers are used to reconstruct the muon and the positron trajectories in μ+→e++νe+vμ decay. A real-time analysis program verifies that the two tracks intersect within the target: this constitutes a very stringent test to veto events which do not correspond to a muon decya. The results of some experiments are given in order to illustrate the field of application of this spectrometer.

The Seebeck coefficient tensor components of arsenic are presented. S11 is positive: holes dominate xy plane transport; S33 is negative: electrons are the more mobile in the z-direction. A quantitative analysis, based on a two-band, multivalley Fermi surface model, is carried through. The partial Fermi energies obtained are Eef = 0.32 eV and Ehf = 0.22 eV and the band overlap is 0.52 eV, results consistent with a Fermi surface in which the electrons occupy fewer pockets than do the holes.

High-resolution three-dimensional (3-D) positron emission tomography (PET) scanners with high count rate performance, such as the quad-high density avalanche chamber (HIDAC), place new demands on image reconstruction algorithms due to the large quantities of high-precision list-mode data which are produced. Therefore, a reconstruction algorithm is required which can, in a practical time frame, reconstruct into very large image arrays (submillimeter voxels, which range over a large field of view) whilst preferably retaining the precision of the data. This work presents an algorithm which meets these demands: one-pass list-mode expectation maximization (OPL-EM) algorithm. The algorithm operates directly on list-mode data, passes through the data once only, accounts for finite resolution effects in the system model, and can also include regularization. The algorithm performs multiple image updates during its single pass through the list-mode data, corresponding to the number of subsets that the data have been split into. The algorithm has been assessed using list-mode data from a quad-HIDAC and is compared to the analytic reconstruction method 3-D reprojection (RP) with 3-D filtered backprojection.

The quad-HIDAC PET scanner offers unparalleled high resolution PET imaging capability (

Magnetoresistivity tensor data in arsenic are analysed using a two carrier, multivalley, ellipsoidal band model. Results agree reasonably with a recent theoretical determination of the Fermi surface. Discrepancies probably arise from the non-ellipsoidal nature of the hole surface.