Dan Evans
PhD Research Presentation

"Parameterized Computational Imaging: Optimized, Data Driven, and Time-Varying Multiphysics Modeling for Image Extension"

Major Professor: Mark Manwaring

Friday, June 26, 10:00 am, JEB 326

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) until computationally predicted parameters match the measured values. Optimization routines are implemented to accelerate the process of finding the new values.