Paper
28 April 2005 Simulated anatomical backgrounds for objective assessment of image quality (OAIQ) in optical tomography
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Abstract
Fluorescence enhanced optical tomography uses modulated NIR light and an exogenous fluorescent contrast agent in order to assess its spatial distribution deep within tissues. However, a spatial distribution of endogenous optical properties of absorption and scattering coefficients arises due to normal, structured anatomical background which can be expected to vary from patient to patient. This structured background can be a source of randomness (or “noise”) in the task of detecting a fluorescent target. In addition, there may be non-uniform distribution of exogenous fluorescent agent. Our objective is to develop the tools for OAIQ in order to assess the performance of image reconstruction algorithms in the presence of anatomical backgrounds owing to both endogenous and exogenous optical properties. We consider the lumpy-object model developed by Rolland and Barrett to simulate the normal background anatomy as a representation of the non-specific distribution of the fluorescent agent as well as the natural heterogeneity of the endogenous tissue optical properties. Reconstructed images show the insensitivity to endogenous optical property lumps in fluorescence enhanced optical imaging. The reconstructed images are more sensitive to uneven distribution of exogenous fluorophore in normal tissues, but can nonetheless be achieved.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amit K. Sahu, Amit Joshi, Ranadhir Roy, and Eva M. Sevick-Muraca "Simulated anatomical backgrounds for objective assessment of image quality (OAIQ) in optical tomography", Proc. SPIE 5693, Optical Tomography and Spectroscopy of Tissue VI, (28 April 2005); https://doi.org/10.1117/12.589188
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KEYWORDS
Optical properties

Tissues

Luminescence

Optical tomography

Atrial fibrillation

Absorption

Detection and tracking algorithms

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