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ETD RECORD
Parameterized computational imaging :optimized, data driven, and time-varying multiphysics modeling for image extension
Citation
Evans, Daniel J.. (2009). Parameterized computational imaging :optimized, data driven, and time-varying multiphysics modeling for image extension. Theses and Dissertations Collection, University of Idaho Library Digital Collections. https://www.lib.uidaho.edu/digital/etd/items/etd_14.html
- Title:
- Parameterized computational imaging :optimized, data driven, and time-varying multiphysics modeling for image extension
- Author:
- Evans, Daniel J.
- Date:
- 2009
- Keywords:
- Diagnostic imaging--Digital techniques
- Program:
- Computer Science
- Abstract:
- The technique of Parameterized Computational Imaging (PCI) allows for a continuous, portable and remote imaging of physiology without the continuous need of complex imaging systems, such as an MRI or CT. The method trades complex imaging equipment for computing power and potentially wireless measured parameters. The PCI algorithm uses a baseline image typically from a high resolution imaging system along with computational models to calculate physically measurable parameters. As the physically measurable parameters change the computational model is iteratively run (feedback loop) with the baseline image being modified until computationally predicted parameters match the measured values. By combining these baseline images with the actual physiological measurements the model can be adjusted to accurately predict the physiology of a particular patient. Then as the sensor measurements are continuously taken, the computational image can be slightly adjusted to match the new values. Optimization routines are implemented to accelerate the process of finding the new values.;Presented in the dissertation are finite element method computational models demonstrating how the PCI algorithm works; for example, a rectangular structure with a moving circular object. The models demonstrate the ability to locate the circular object with a few point measurements. The presented computational model uses swarm optimization to help recreate the circular object image from the measured data. This dissertation also introduces the different technology that make PCI feasible, including computer power, image segmentation, wireless technology, sensor fusion, computational models and database systems. The dissertation focuses on the impact of multiphysics and time varying computational parameters on PCI theory.
- Description:
- Thesis (Ph. D., Computer Science)--University of Idaho, August 2009.
- Major Professor:
- Mark L. Manwaring.
- Defense Date:
- August 2009.
- Type:
- Text
- Format Original:
- xv, 214 leaves :col. ill. ;29 cm.
- Format:
- record
Rights
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