Speaker
Giovanni Di Domenico
(FE)
Description
The Common Unified Device Architecture (CUDA) is a NVIDIA software development platform that allows us to implement general-purpose applications on graphics processing unit (GPU). There are a lot of application areas that benefit of the GPU computing. Fast 3D cone-beam reconstruction is required by many application fields like medical CT imaging or industrial non-destructive testing. For that reason, researchers work on hardware optimized 3D reconstruction algorithms to reduce the reconstruction time. We have used GPU hardware and CUDA platform to speed-up the Feldkamp Davis Kress (FDK) algorithm, which permits the reconstruction of cone-beam CT data. In this work, we present our implementation of the most time-consuming step of FDK algorithm: filtering and back-projection. We also show the required steps needed to be done for parallelization of the algorithm on the CUDA architecture. Our FDK algorithm implementation in addition allows to do a rapid reconstruction, which means that the reconstructed data is ready just after the end of data acquisition.
Primary author
Giovanni Di Domenico
(FE)
