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.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/144580 |
| Date | January 2011 |
| Creators | Trumbull, Tara |
| Contributors | Kupinski, Matthew, Clarkson, Eric, Furenlid, Lars, Barrett, Harrison H |
| Publisher | The University of Arizona. |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis, text |
| Rights | Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author. |
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