Filtered back projection on shared-memory multiprocessors

Abstract Filtered back projection is a popular algorithm for the reconstruction of n -dimensional signals from their ( n -1)-dimensional projections (in the sense of line integrals). Here we specifically treat the problem of the three-dimensional (3D) reconstruction of an object from its two-dimensional (2D) projection images. In this work we analyze the implementation of the filtered back projection method in shared-memory multiprocessor systems. The resulting parallel algorithm turns out to be scalable as the result of the use of large/medium granularity and an adequate allocation ofdata on the processors. A number of experimental results (such as run time, speed-up and efficiency) on a BBN Butterfly are also reported.