A Born Type iterative method for imaging of heterogeneous scattering media and its application to simulated breast tissue

Yuqi Yao, Yaling Pei, Yao Wang, Randall L. Barbour

Research output: Contribution to journalConference articlepeer-review

Abstract

In this paper, we present a Born-Type iterative algorithm for reconstruction of absorption and diffusion coefficient distributions of a heterogeneous scattering medium. This method is derived based on the integral form of the diffusion equation for the photon flux. It takes into account the nonlinear nature of the problem by using an iterative perturbation approach. Within each iteration, the forward problem (update of the total field and Green's function) is solved by the finite element method (FEM), and the inverse problem (update of the medium properties) is obtained by a regularized least squares method. This method has been used to reconstruct "pathologies" embedded in an inhomogeneous test medium simulating a normal female breast from frequency domain data. The test medium is constructed by assigning optical coefficients according to a MR derived anatomical map. Our simulation results show that the algorithm is computationally practical and can yield qualitatively and quantitatively correct absorption and scattering distributions of embedded objects from simulated data with up to 5% additive noise in the simulated measurement data.

Original languageEnglish (US)
Pages (from-to)232-240
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2979
DOIs
StatePublished - 1997
EventProceedings of Optical Tomography and Spectroscopy of Tissue: Theory, Instrumentation, Model and Human Studies II - San Jose, CA, United States
Duration: Feb 9 1997Feb 12 1997

Keywords

  • Born approximation
  • CGD method
  • Diffusion model
  • Finite element method
  • Image reconstruction
  • Inverse scattering
  • Optical imaging

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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