Fast parallel algorithm for three-dimensional distance-driven model in iterative computed tomography reconstruction

The projection matrix model is used to describe the physical relationship between reconstructed object and projection.Such a model has a strong influence on projection and backprojection,two vital operations in iterative computed tomographic reconstruction.The distance-driven model（DDM） is a state-of-the-art technology that simulates forward and back projections.This model has a low computational complexity and a relatively high spatial resolution;however,it includes only a few methods in a parallel operation with a matched model scheme.This study introduces a fast and parallelizable algorithm to improve the traditional DDM for computing the parallel projection and backprojection operations.Our proposed model has been implemented on a GPU（graphic processing unit） platform and has achieved satisfactory computational efficiency with no approximation.The runtime for the projection and backprojection operations with our model is approximately 4.5 s and 10.5 s per loop,respectively,with an image size of 256×256×256 and 360 projections with a size of 512×512.We compare several general algorithms that have been proposed for maximizing GPU efficiency by using the unmatched projection/backprojection models in a parallel computation.The imaging resolution is not sacrificed and remains accurate during computed tomographic reconstruction.

Position coordinates-based iterative reconstruction for robotic CT

Purpose Robotic CTs can achieve customized trajectory scanning with x-ray tube and detector held by flexible robotic arms rather than fixed rails or gantry.However,the motion errors of the robotic arms cannot be neglected.Hence,the reconstruction method of Robotic CTs should be suitable for arbitrary trajectory and should take motion errors into full consideration.Method In this paper,we present an iterative reconstruction method for robotic CT systems.Unlike the analytical algorithms,such as FDK,this method makes no assumption about the scan trajectory.The projection and backprojection operations are modeled by 3D distance-driven algorithm using the coordinates of x-ray source and detector center fed back from the robotic arm’s positioning system directly.Both numerical simulations and practical experiments are conducted to verify the effectiveness of this method in arbitrary trajectory reconstruction and motion errors correction for robotic CT systems.Results For our non-circular and non-planar trajectory scan,this proposed method could easily handle the reconstruction and obtain a result comparable to reference.In addition,for 0.1%motion errors,using the proposed method could improve the reconstruction quality,and the RMSE could be reduced by 30%.Conclusions This iterative reconstruction method is suitable for arbitrary trajectory scans and can decrease the degradation of image quality caused by motion errors of robotic arm.