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We present a scalable, cost-effective, and compact high voltage (HV) distribution design for a system that requires many HV channels for photodetector biasing. A digital-to-analog converter (DAC) with a 100 V output range is floated with its reference at - 1800~\V, providing outputs between - 1800~\V and - 1700~\V. As a consequence, the DAC control and power signals are referenced to - 1800~\V. This design was implemented in our 1 mm resolution clinical PET imaging system with detectors comprised of LYSO scintillation crystals coupled to position-sensitive avalanche photodiodes (PSAPDs). The programmable bias voltage outputs have only 20 ~\m~\Vpp of bias ripple. This design enables all PSAPDs to be biased at their optimal bias voltage, allowing us to achieve a standard deviation of only 2.3% in the energy resolution measured across all 512 PSAPDs in the subsystem. [ABSTRACT FROM AUTHOR]

We analyze performance of position sensitive detectors such as Position Sensitive Avalanche Photodiodes (PSAPDs) used to readout pixelated scintillation crystal arrays. Crystal identification abilities are determined by analyzing the flood histogram. A good flood histogram has peaks which are as well separated and as narrow as possible since this enables better crystal identification, and ultimately improves spatial resolution. We present a signal conditioning circuit for the readout of PSAPDs and investigate how the tradeoff between the parameters of the signal conditioning circuit components, the PSAPD bias voltage, and the input dynamic range and noise of the preamplifier influence the flood histogram. The signal conditioning circuit involves adding a resistor and a capacitor between the four spatial channels of the detector and the preamplifier. This technique was verified and studied both experimentally and by simulation using PSAPDs coupled to 8 \times 8 arrays of 1 mm^3 scintillation crystals. Results showed that the flood histogram is not very sensitive to the exact value of the resistor in the signal conditioning circuit, but in general a resistance about twice the sheet resistance of the position sensitive detector is recommended. The capacitor in the signal conditioning circuit should be chosen by taking preamplifier input dynamic range, preamplifier noise, and detector noise into account. [ABSTRACT FROM PUBLISHER]

We are developing a dual panel breast-dedicated positron emission tomography (PET) system using LSO scintillators coupled to position sensitive avalanche photodiodes (PSAPD). The charge output is amplified and read using NOVA RENA-3 ASICs. This paper shows that the coincidence timing resolution of the RENA-3 ASIC can be improved using certain list-mode calibrations. We treat the calibration problem as a convex optimization problem and use the RENA-3's analog-based timing system to correct the measured data for time dispersion effects from correlated noise, PSAPD signal delays and varying signal amplitudes. The direct solution to the optimization problem involves a matrix inversion that grows order (n^3) with the number of parameters. An iterative method using single-coordinate descent to approximate the inversion grows order (n). The inversion does not need to run to convergence, since any gains at high iteration number will be low compared to noise amplification. The system calibration method is demonstrated with measured pulser data as well as with two LSO-PSAPD detectors in electronic coincidence. After applying the algorithm, the 511 keV photopeak paired coincidence time resolution from the LSO-PSAPD detectors under study improved by 57%, from the raw value of 16.3 \pm 0.07 ns full-width at half-maximum (FWHM) to 6.92 \pm 0.02 ns FWHM (11.52 \pm 0.05 ns to 4.89 \pm 0.02 ns for unpaired photons). [ABSTRACT FROM AUTHOR]

Implementation of real-time neural network inversion on the SRC-6e, a computer that uses multiple field-programmable gate arrays (FPGAs) as reconfigurable computing elements, is examined using a sonar application as a specific case study. A feedforward multilayer perceptron neural network is used to estimate the performance of the sonar system (Jung et al., 2001). A particle swarm algorithm uses the trained network to perform a search for the control parameters required to optimize the output performance of the sonar system in the presence of imposed environmental constraints (Fox et al., 2002). The particle swarm optimization (PSO) requires repetitive queries of the neural network. Alternatives for implementing neural networks and particle swarm algorithms in reconfigurable hardware are contrasted. The final implementation provides nearly two orders of magnitude of speed increase over a state-of-the-art personal computer (PC), providing a real-time solution. [ABSTRACT FROM AUTHOR]

Microelectromechanical systems (MEMS) electrostatic-based transducers inherently produce harmonics as the electrostatic force generated in the transmit mode is approximately proportional to the square of the applied voltage signal. This characteristic precludes them from being effectively used for harmonic imaging (either with or without the addition of microbubble-based contrast agents). The harmonic signal that is nonlinearly generated by tissue (or contrast agent) cannot be distinguished from the inherent transmitted harmonic signal. We investigated two precompensation methods to cancel this inherent harmonic generation in electrostatic transducers. A combination of finite element analysis (FEA) and experimental results are presented. The first approach relies on a calculation, or measurement, of the transducer's linear transfer function, which is valid for small signal levels. Using this transfer function and a measurement of the undesired harmonic signal, a predistorted transmit signal was calculated to cancel the harmonic inherently generated by the transducer. Due to the lack of perfect linearity, the approach does not work completely in a single iteration. However, with subsequent iterations, the problem becomes more linear and converges toward a very satisfactory result (a 18.6 dB harmonic reduction was achieved in FEA simulations and a 20.7 dB reduction was measured in a prototype experiment). The second approach tested involves defining a desired function [including a direct current (DC) offset], then taking the square root of this function to determine the shape of the required input function. A 5.5 dB reduction of transmitted harmonic was obtained in both FEA simulation and experimental prototypes test. [ABSTRACT FROM AUTHOR]

Laser-based, thermoelastic transduction methods have potential in very high frequency (>50 MHz), high-density two-dimensional (2-D) arrays for a variety of very high-resolution superficial imaging applications, including in vivo tissue sectioning. Previous studies of these transducers generally have been based on experimental measurements or theoretical analyses using various simplifying assumptions. These theoretical models are mostly 1-D and best matched to simple geometries with a minimum number of component materials. In this work, we use a new thermoelastic solver in a commercially available finite-element analysis (FEA) software package to analyze multidimensional effects in laser-based devices of arbitrary geometry with the potential for use with arbitrary material properties. The FEA approach was verified first against experimental data. Thereafter, we explored the impact of various design variables, including laser spot size and laser penetration depth. [ABSTRACT FROM AUTHOR]

Reports that the isotach network was designed to reduce the cost of synchronization in parallel computation. How the network allows processes to pipeline operations; Other uses of the network; Details on empirical and analytic studies of isotach synchronization techniques.