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Reconstructing absorption and diffusion shape profiles in optical tomography by a level set technique.

M Schweiger1, S R Arridge, O Dorn

  • 1Department of Computer Science, University College London, Gower Street, London WC1E 6BT, UK. M.Schweiger@cs.ucl.ac.uk

Optics Letters
|February 25, 2006
PubMed
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This study introduces a novel shape reconstruction algorithm for optical tomography, enabling simultaneous recovery of object shapes and their optical properties from noisy data.

Area of Science:

  • Biomedical Optics
  • Computational Imaging
  • Inverse Problems

Background:

  • Optical tomography faces challenges in accurately reconstructing object shapes and optical properties.
  • Existing methods often struggle with simultaneous recovery in heterogeneous media.

Purpose of the Study:

  • To develop and validate a new level-set-based algorithm for shape reconstruction in optical tomography.
  • To simultaneously recover the shapes and optical parameters (absorption and diffusion) of embedded objects.

Main Methods:

  • Utilizes a level-set formulation to represent object shapes.
  • Derives evolution laws based on gradient directions of a cost functional.
  • Applies two distinct level-set functions for absorption and diffusion parameters.

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Main Results:

  • Successfully recovers shapes and contrast values of absorbing and scattering objects.
  • Demonstrates efficacy in 2D numerical experiments with simulated noisy data.
  • Shows robustness in a moderately heterogeneous background medium.

Conclusions:

  • The proposed level-set algorithm effectively reconstructs shapes and optical properties simultaneously.
  • This method offers a promising approach for advanced optical tomography applications.
  • The algorithm's ability to handle noisy data and heterogeneous backgrounds is a key advancement.