Multistage parallel algorithm for diffraction tomography

Abstract

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.

Optical coherence tomography

“…Hence at reference mirror position zϭd, the interference term equals the real part of the convolution of the scattering potential F(z) with the coherence function g (1) () of the light used: 8) i.e., the coherence function obviously plays the role of a point spread function (PSF).…”

“…6,7 Much attention has also been paid to the development of further algorithms. 4,8 One-dimensional and two-dimensional optical reconstructions of cross-sectional images of an object were obtained from holographically recorded scattered field data nearly two decades ago. 9,10 These first attempts, however, were not further extended at that time because no spatially coherent broadband light sources were available.…”