Computationally efficient and statistically robust image reconstruction in three-dimensional diffraction tomography

Mark A. Anastasio, Xiaochuan Pan

Research output: Contribution to journalArticle

Abstract

Diffraction tomography (DT) is an inversion scheme used to reconstruct the spatially variant refractive-index distribution of a scattering object. We developed computationally efficient algorithms for image reconstruction in three-dimensional (3D) DT. A unique and important aspect of these algorithms is that they involve only a series of two-dimensional reconstructions and thus greatly reduce the prohibitively large computational load required by conventional 3D reconstruction algorithms. We also investigated the noise characteristics of these algorithms and developed strategies that exploit the statistically complementary information inherent in the measured data to achieve a bias-free reduction of the reconstructed image variance. We performed numerical studies that corroborate our theoretical assertions.

Original languageEnglish (US)
Pages (from-to)391-400
Number of pages10
JournalJournal of the Optical Society of America A: Optics and Image Science, and Vision
Volume17
Issue number3
DOIs
StatePublished - Mar 2000
Externally publishedYes

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Computer Vision and Pattern Recognition

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