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Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers
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Quantification in time-domain diffuse optical tomography using Mellin-Laplace transforms.

Judy Zouaoui1, Laura Di Sieno2, Lionel Hervé1

  • 1Univ. Grenoble Alpes, F-38000 Grenoble, France CEA, LETI, MINATEC Campus, F-38054 Grenoble, France.

Biomedical Optics Express
|November 22, 2016
PubMed
Summary
This summary is machine-generated.

Time-domain diffuse optical tomography can quantify absorption changes in turbid media. Accuracy improves by constraining absorption changes to the inclusion

Keywords:
(030.5260) Photon counting(100.3010) Image reconstruction techniques(110.0113) Imaging through turbid media(110.6960) Tomography(170.6920) Time-resolved imaging(230.5160) Photodetectors

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Area of Science:

  • Biomedical Optics
  • Medical Imaging
  • Photon Transport

Background:

  • Diffuse optical tomography (DOT) is a non-invasive imaging technique.
  • Accurate quantification of optical properties in scattering media remains challenging.

Purpose of the Study:

  • To evaluate time-domain DOT with Mellin-Laplace transforms for quantifying absorption perturbations.
  • To assess the impact of inclusion depth and absorption change on quantification accuracy.

Main Methods:

  • Numerical simulations and phantom experiments were conducted.
  • Time-domain diffuse optical tomography utilizing Mellin-Laplace transforms was employed.
  • Quantification of absorption coefficient changes (δμa) for centimetric objects at varying depths (1-2 cm) in turbid media.

Main Results:

  • Estimated absorption coefficient showed near-linear behavior for changes up to 0.15 cm⁻¹.
  • Underestimation factors of ~2, 3, and 6 were observed at depths of 1.0, 1.5, and 2.0 cm, respectively.
  • Sublinear variation and ~20% decrease in accuracy were noted for larger absorption changes (δμa = 0.37 cm⁻¹).

Conclusions:

  • Time-domain DOT with Mellin-Laplace transforms can quantify absorption perturbations.
  • Inclusion depth significantly impacts quantification accuracy, leading to underestimation.
  • Constraining absorption change to the inclusion volume can substantially enhance reconstruction accuracy and linearity.