We have developed a simulation of the AdaptiSPECT small-animal Single Photon Emission Computed Tomography (SPECT) imaging system. The simulation system is entitled SimAdaptiSPECT and is written in C, NVIDIA CUDA, and Matlab. Using this simulation, we have accomplished an analysis of the Scanning Linear Estimation (SLE) technique for estimating tumor parameters, and calculated sensitivity information for AdaptiSPECT configurations.SimAdaptiSPECT takes, as input, simulated mouse phantoms (generated by MOBY) contained in binary files and AdaptiSPECT configuration geometry contained in ASCII text files. SimAdaptiSPECT utilizes GPU parallel processing to simulate AdaptiSPECT images. SimAdaptiSPECT also utilizes GPU parallel processing to perform 3-D image reconstruction from 2-D AdaptiSPECT camera images (real or simulated), using a novel variant of the Ordered Subsets Expectation Maximization (OSEM) algorithm. Methods for generating the inputs, such as a population of randomly varying numerical mouse phantoms with randomly varying hepatic lesions, are also discussed.

Thesis (Ph. D.)--University of California, Riverside, 2009. / Includes abstract. Available via ProQuest Digital Dissertations. Title from first page of PDF file (viewed March 16, 2010). Includes bibliographical references. Also issued in print.

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Ultrasonic guided wave imaging methods offer a cost-effective mechanism to perform in situ structural health monitoring (SHM) of large plate-like structures, such as commercial aircraft skins, ship hulls, storage tanks, and civil structures. However, current limits in imaging quality, environmental sensitivities, and implementation costs, among other things, are preventing widespread commercial adoption. The research presented here significantly advances state of the art guided wave imaging techniques using inexpensive, spatially distributed arrays of piezoelectric transducers. Novel adaptive imaging techniques are combined with in situ estimation and compensation of propagation parameters; e.g., dispersion curves and transducer transfer functions, to reduce sensitivity to unavoidable measurement inaccuracies and significantly improve resolution and reduce artifacts in guided wave images. The techniques can be used not only to detect and locate defects or damage, but also to characterize the type of damage. The improved ability to detect, locate, and now characterize defects or damage using a sparse array of ultrasonic transducers is intended to assist in the establishment of in situ guided wave imaging as a technically and economically viable tool for long-term monitoring of plate-like engineering structures.