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

A shape reconstruction algorithm for optical tomography is introduced that uses a level-set formulation for the shapes. Evolution laws based on gradient directions for a cost functional are derived for two different level-set functions, one describing the absorption and one the diffusion parameter,...

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Bibliographic Details
Published in:Optics letters 2006-02, Vol.31 (4), p.471-473
Main Authors: SCHWEIGER, M, ARRIDGE, S. R, DORN, O, ZACHAROPOULOS, A, KOLEHMAINEN, V
Format: Article
Language:English
Subjects:
Absorption
Algorithms
Computer Simulation
Diffusion
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image reconstruction
tomography
Imaging and optical processing
Information Storage and Retrieval - methods
Models, Biological
Optics
Physics
Reproducibility of Results
Sensitivity and Specificity
Tomography, Optical - methods
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Summary:A shape reconstruction algorithm for optical tomography is introduced that uses a level-set formulation for the shapes. Evolution laws based on gradient directions for a cost functional are derived for two different level-set functions, one describing the absorption and one the diffusion parameter, as well as for the parameter values inside these shapes. Numerical experiments are presented in 2D that show that the new method is able to simultaneously recover shapes and contrast values of absorbing and scattering objects embedded in a moderately heterogeneous background medium from simulated noisy data.
ISSN:0146-9592
1539-4794
DOI:10.1364/OL.31.000471