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An X-ray computed tomography (CT) simulator based on Geant4 toolkit was developed for simulation of both fan- and cone-beam CT scanners. There major components X-ray tube, phantom and detector are simulated. Different to analytical simulation, this simulation is accordance with imaging physics by adopting the Geant4 toolkit. Compared with ordinary statistical simulation, acceleration investigation...
In this paper we study a Markov Chain Monte Carlo (MCMC) Gibbs sampler for solving the integer least-squares problem. In digital communication the problem is equivalent to performing maximum likelihood (ML) detection in multiple-input multiple-output (MIMO) systems. While the use of MCMC methods for such problems has already been proposed, our method is novel in that we optimize the "temperature"...
We present an on-line list-mode image reconstruction system using GPUs for a surgical PET imaging probe system. We used the nVidia GeForce 9800GTX+ and CUDA to reconstruct images. The proposed system can generate a three-dimensional image from simulated data in 70 msec. We also compared the processing time with respect to the number of LORs per subset. We are working on optimizing the CUDA code to...
Compton cameras have been used for astronomical and medical imaging applications as early as the 1970s. Recent interest in their potential for the detection and localization of special nuclear material (SNM) has led to increasing investigations. In this work, a specialized algorithm was developed for the optimization of a two-plane Compton camera. The MCNP-PoliMi code was utilized to simulate photon...
In radiotherapy simulations, Monte Carlo-based radiotherapy simulation is applied to a high accurate calculation of dose distributions in a patient or optimization of the beam delivery system. Geant4 toolkit has come to be utilized to build a Monte Carlo simulator for that purpose. It needs the volume rendering capability to display a complex volume data by a visualizer. However, there is no volume...
We have built a four-layer detector to obtain the depth of interaction (DOI) information in which all four layers have a relative offset of a half crystal pitch with each other. The main characteristics of the detector, especially the energy and spatial resolutions, strongly depend on the crystal surface treatments. As a part of the work for the development of an animal PET, we have investigated the...
In order to establish a brain-machine interface (BMI) system that rehabilitates damaged cerebellum function of discrete motor learning, the detection of conditional and unconditional stimuli (CS and US) onset times based on electro-physiology recordings analysis is necessary. These signals are relayed through brainstem areas called Pontine Nucleus (PN) and the Inferior Olive (IO) respectively. In...
This paper presents Sandia National Laboratories' Outdoor Weapons of Mass Destruction Decision Analysis Center (OutDAC) and, through an example case study, derives lessons for its use. This tool, related to similar capabilities at Sandia, can be used to determine functional requirements for a detection system of aerosol-released threats outdoors. Essential components of OutDAC are a population database,...
We explore the feasibility of low probability of intercept for sonar signals. Using a noise-like active sonar signal, the transmitter (platform) employs a matched filter for echo detection while the target is assumed to use an energy detector. Decision statistic distributions are developed at both the platform and target. These distributions allow efficient Monte Carlo simulation of detection performance...
The optimization of the injected dose in PET imaging systems is important for the design of clinical data acquisition protocols. Methods to reduce the total amount of radioactive dose injected into a patient are investigated. On the other hand, a lower dose may require a longer data acquisition time to obtain images of high statistical quality, thus limiting the total number of PET scans performed...
The problem of instantaneous threshold optimization is studied. Over the earlier formulation of the problem, for Neyman-Pearson detector a closed-form solution is developed. The proposed solution provides a low-cost computational approach for setting the false alarm rate of the detector in each tracking instant instead of setting it constantly. The results are validated through experiments.
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