HPC for iterative image reconstruction in CT
Proceedings of the 2008 C3S2E conference
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Abstract: Three dimensional computed tomography is a computationally intensive procedure, requiring large amounts of RAM and processing power. Parallel methods for two dimensional computed tomography have been studied, but not extended or applied to 3D cone beam tomography. A discussion on how the 3D cone beam tomography problem can be implemented in parallel using MPI is given. We show an improvement in performance from 58.2% to 81.8% processor utilization in a heterogeneous cluster of workstations by load balancing. A 96.8% efficiency was seen using a 2 processor SMP.