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3D shape based reconstruction of experimental data in Diffuse Optical Tomography
Author(s) -
Athanasios Zacharopoulos,
Martin Schweiger,
Ville Kolehmainen,
Simon Arridge
Publication year - 2009
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.17.018940
Subject(s) - diffuse optical imaging , iterative reconstruction , spherical harmonics , imaging phantom , optics , inverse problem , scattering , tomography , tomographic reconstruction , optical tomography , finite element method , a priori and a posteriori , reconstruction algorithm , physics , algorithm , computer science , mathematical analysis , mathematics , computer vision , philosophy , epistemology , thermodynamics
Diffuse optical tomography (DOT) aims at recovering three-dimensional images of absorption and scattering parameters inside diffusive body based on small number of transmission measurements at the boundary of the body. This image reconstruction problem is known to be an ill-posed inverse problem, which requires use of prior information for successful reconstruction. We present a shape based method for DOT, where we assume a priori that the unknown body consist of disjoint subdomains with different optical properties. We utilize spherical harmonics expansion to parameterize the reconstruction problem with respect to the subdomain boundaries, and introduce a finite element (FEM) based algorithm that uses a novel 3D mesh subdivision technique to describe the mapping from spherical harmonics coefficients to the 3D absorption and scattering distributions inside a unstructured volumetric FEM mesh. We evaluate the shape based method by reconstructing experimental DOT data, from a cylindrical phantom with one inclusion with high absorption and one with high scattering. The reconstruction was monitored, and we found a 87% reduction in the Hausdorff measure between targets and reconstructed inclusions, 96% success in recovering the location of the centers of the inclusions and 87% success in average in the recovery for the volumes.

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