A multistage parallel algorithm with iterative processing is discussed for the processing of information in diffraction tomography. The algorithm is based on matrix partitioning, which results in mostly parallel stages of processing. Each successive stage is designed to minimize the remaining error. The process is iterated until convergence. The major advantages of the multistage algorithm are the reduced computational time from faster convergence as compared with a single-stage iterative algorithm, further reduction of computation time if the stages are implemented mostly in parallel, and better performance in terms of reduced reconstruction error.