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Computed Tomography-guided Time-domain Diffuse Fluorescence Tomography in Small Animals for Localization of Cancer Biomarkers

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Compensation of optode sensitivity and position errors in diffuse optical tomography using the approximation error

Meghdoot Mozumder¹, Tanja Tarvainen, Simon R Arridge

¹Department of Applied Physics, University of Eastern Finland P.O. Box 1627, 70211 Kuopio, Finland.

Biomedical Optics Express

|October 25, 2013

Summary

This summary is machine-generated.

Diffuse optical tomography (DOT) reconstruction is sensitive to errors. This study shows that approximation error theory can correct image artifacts caused by inaccurate optode positions and coupling in DOT.

Keywords:

(100.3190) Inverse problems (170.3010) Image reconstruction techniques (170.6960) Tomography (290.7050) Turbid media

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Area of Science:

Biomedical optics
Medical imaging
Computational modeling

Background:

Diffuse optical tomography (DOT) is a powerful imaging technique but is highly sensitive to measurement and modeling errors.
Inaccurate source/detector coupling and positions introduce significant artifacts in reconstructed DOT images.
Approximation error theory offers a potential framework for addressing modeling errors in DOT.

Purpose of the Study:

To investigate the feasibility of approximation error theory for compensating DOT modeling errors.
To evaluate the approach's effectiveness in correcting artifacts from inaccurately known optode locations and coupling coefficients.

Main Methods:

Simulations were used to evaluate the approximation error approach.
The method was tested for its ability to handle errors in optode coupling and position data.

Main Results:

The approximation error method demonstrated effectiveness in recovering from image artifacts.
Simulations confirmed that the approach can compensate for errors in optode coupling and position.

Conclusions:

Approximation error theory is a viable method for mitigating artifacts in DOT reconstructions caused by optode positioning and coupling inaccuracies.
This approach can improve the reliability and accuracy of DOT imaging.