The Advanced GAmma Tracking Array (AGATA) is a European project to develop and operate the next generation γ-ray spectrometer. AGATA is based on the technique of γ-ray energy tracking in electrically segmented high-purity germanium crystals. This technique requires the accurate determination of the energy, time and position of every interaction as a γ ray deposits its energy within the detector volume. Reconstruction of the full interaction path results in a detector with very high efficiency and excellent spectral response. The realisation of γ-ray tracking and AGATA is a result of many technical advances. These include the development of encapsulated highly segmented germanium detectors assembled in a triple cluster detector cryostat, an electronics system with fast digital sampling and a data acquisition system to process the data at a high rate. The full characterisation of the crystals was measured and compared with detector-response simulations. This enabled pulse-shape analysis algorithms, to extract energy, time and position, to be employed. In addition, tracking algorithms for event reconstruction were developed. The first phase of AGATA is now complete and operational in its first physics campaign. In the future AGATA will be moved between laboratories in Europe and operated in a series of campaigns to take advantage of the different beams and facilities available to maximise its science output. The paper reviews all the achievements made in the AGATA project including all the necessary infrastructure to operate and support the spectrometer
Three time memory tradeoff algorithms are compared in this paper. Specifically, the classical tradeoff algorithm by Hellman, the distinguished point tradeoff method, and the rainbow table method, in their non-perfect table versions, are treated.We show that, under parameters and assumptions that are typically considered in theoretic discussions of the tradeoff algorithms, Hellman and distinguished point tradeoffs perform very close to each other and that the rainbow table method performs somewhat better than the other two algorithms. Our method of comparison can easily be applied to other situations, where the conclusions could be different.The analysis of tradeoff efficiency presented in this paper does not ignore the effects of false alarms and also covers techniques for reducing storage, such as ending point truncations and index tables. Our comparison of algorithms takes the success probabilities and pre-computation efforts fully into account.
It has been suggested that a Compton camera should be used in single photon emission computed tomography because a conventional gamma camera has low efficiency. It brings about a cone transform, which maps a function onto the set of its surface integrals over cones determined by the detector position, the central axis, and the opening angle of the Compton camera. We provide inversion formulas using complete Compton data for three-and two-dimensional cases. Numerical simulations are presented to demonstrate the suggested algorithms in dimension two. Also, we discuss other inversions and the stability estimates of a cone transform with a fixed central axis.
Single photon emission computed tomography (SPECT) is a well established clinical tool for functional imaging. A limitation of current SPECT systems is the use of mechanical collimation, where only a small fraction of the emitted photons is actually used for image reconstruction. This results in large noise level and finally in a limited spatial resolution. In order to decrease the noise level and to increase the imaging resolution, Compton cameras have been proposed as an alternative to mechanical collimators. Image reconstruction in SPECT with Compton cameras yields to the problem of recovering a marker distribution from integrals over conical surfaces. Due to this and other applications, such conical Radon transforms recently got significant attention. In the current paper we consider the case where the cones of integration have vertices on a circular cylinder and axis pointing to the symmetry axis of the cylinder. As main results we derive analytic reconstruction methods for the considered transform. We also investigate the V-line transform with vertices on a circle and symmetry axis orthogonal to the circle, which arises in the special case where the absorber distribution is located in a horizontal plane.
Increasing the imaging speed is a central aim in photoacoustic tomography. This issue is especially important in the case of sequential scanning approaches as applied for most existing optical detection schemes. In this work we address this issue using techniques of compressed sensing. We demonstrate, that the number of measurements can significantly be reduced by allowing general linear measurements instead of point-wise pressure values. A main requirement in compressed sensing is the sparsity of the unknowns to be recovered. For that purpose we develop the concept of sparsifying temporal transforms for three-dimensional photoacoustic tomography. We establish a two-stage algorithm that recovers the complete pressure signals in a first step and then applies a standard reconstruction algorithm such as backprojection. This yields a novel reconstruction method with much lower complexity than existing compressed sensing approaches for photoacoustic tomography. Reconstruction results for simulated and for experimental data verify that the proposed compressed sensing scheme allows to significantly reducing the number of spatial measurements without reducing the spatial resolution.
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