Image reconstruction from nonuniformly spaced samples in Fourier domain optical coherence tomography

Jun Ke, Rui Zhu, Edmund Y. Lam*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this work, we use inverse imaging for object reconstruction from nonuniformly-spaced samples in Fourier domain optical coherence tomography (FD-OCT). We first model the FD-OCT system with a linear system of equations, where the source power spectrum and the nonuniformly-spaced sample positions are represented accurately. Then, we reconstruct the object signal directly from the nonuniformly-spaced wavelength measurements. With the inverse imaging method, we directly estimate the 2D cross-sectional object image instead of a set of independent A-line signals. By using the Total Variation (TV) as a constraint in the optimization process, we reduce the noise in the 2D object estimation. Besides TV, object sparsity is also used as a regularization for the signal reconstruction in FD-OCT. Experimental results demonstrate the advantages of our method, as we compare it with other methods.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Computational Imaging X
DOIs
Publication statusPublished - 2012
Externally publishedYes
EventComputational Imaging X - Burlingame, CA, United States
Duration: 23 Jan 201224 Jan 2012

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8296
ISSN (Print)0277-786X

Conference

ConferenceComputational Imaging X
Country/TerritoryUnited States
CityBurlingame, CA
Period23/01/1224/01/12

Keywords

  • Fourier domain optical coherence tomography (FD-OCT)
  • L norm
  • inverse imaging
  • nonuniform discrete Fourier transform (NUDFT)
  • total variation (TV)

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