Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2007 · 14 citations · 0 references
EngineeringComputer EngineeringComputer ScienceDiagnostic RadiologyField-programmable Gate ArraysInterventional RadiologyComputed TomographyField-programmable Gate Array ArchitectureGraphics Processing UnitsHardware AccelerationImage ReconstructionMedical ImagingBackprojectionCone-beam Computed Tomography ReconstructionField-programmable Gate Array AccelerationField-programmable Gate Array AcceleratorsField-programmable Gate Arrays (Fpgas)Parallel ProcessingReconstruction AlgorithmsThree-dimensional Image Reconstruction
The three-dimensional image reconstruction process used in interventional CT imaging is computationally demanding. Implementation on general-purpose computational platforms requires a substantial time, which is undesirable during time-critical surgical and minimally invasive procedures. Field Programmable Gate Arrays (FPGA)s and Graphics Processing Units (GPU)s have been studied as a platform to accelerate 3-D imaging. FPGA and GPU devices offer a reprogrammable hardware architecture, configurable for pipelining and high levels of parallel processing to increase computational throughput, as well as the benefits of being off-the-shelf and effective 'performance-to-watt' solutions. The main focus of this paper is on the backprojection step of the image reconstruction process, since it is the most computationally intensive part. Using the popular Feldkamp-Davis-Kress (FDK) cone-beam algorithm, our studies indicate the entire 256<sup>3</sup> image reconstruction process can be accelerated to real or near real-time (i.e. immediately after a finished scan of 15-30 seconds duration) on a mobile X-ray C-arm system using available resources on built-in FPGA board. High resolution 512<sup>3 </sup>image backprojection can be also accomplished within the same scanning time on a high-end GPU board comprising up to 128 streaming processors.