Parallel computing approach for efficient 3-D X-ray-simulated image reconstruction

Accurate 3-dimensional (3-D) reconstruction technology for nondestructive testing based on digital radiography (DR) is of great importance for alleviating the drawbacks of the existing computed tomography (CT)-based method. The commonly used Monte Carlo simulation method ensures well-performing imaging results for DR. However, for 3-D reconstruction, it is limited by its high time consumption. To solve this problem, this study proposes a parallel computing method to accelerate Monte Carlo simulation for projection images with a parallel interface and a specific DR application. The images are utilized for 3-D reconstruction of the test model. We verify the accuracy of parallel computing for DR and evaluate the performance of two parallel computing modes-multithreaded applications (G4-MT) and message-passing interfaces (G4-MPI)-by assessing parallel speedup and efficiency. This study explores the scalability of the hybrid G4-MPI and G4-MT modes. The results show that the two parallel computing modes can significantly reduce the Monte Carlo simulation time because the parallel speedup increment of Monte Carlo simulations can be considered linear growth, and the parallel efficiency is maintained at a high level. The hybrid mode has strong scalability, as the overall run time of the 180 simulations using 320 threads is 15.35 h with 10 billion particles emitted, and the parallel speedup can be up to 151.36. The 3-D reconstruction of the model is achieved based on the filtered back projection (FBP) algorithm using 180 projection images obtained with the hybrid G4-MPI and G4-MT. The quality of the reconstructed sliced images is satisfactory because the images can reflect the internal structure of the test model. This method is applied to a complex model, and the quality of the reconstructed images is evaluated.