Open Access
1 September 2005 Contrast-detail analysis characterizing diffuse optical fluorescence tomography image reconstruction
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Abstract
Contrast-detail analysis is used to evaluate the imaging performance of diffuse optical fluorescence tomography (DOFT), characterizing spatial resolution limits, signal-to-noise limits, and the trade-off between object contrast and size. Reconstructed images of fluorescence yield from simulated noisy data were used to determine the contrast-to-noise ratio (CNR). A threshold of CNR=3 was used to approximate a lowest acceptable noise level in the image, as a surrogate measure for human detection of objects. For objects 0.5 cm inside the edge of a simulated tissue region, the smallest diameter that met this criteria was approximately 1.7 mm, regardless of contrast level, and test field diameter had little impact on this limit. Object depth had substantial impact on object CNR, leading to a limit of 4 mm for objects near the center of a 51-mm test field and 8.5 mm for an 86-mm test field. Similarly, large objects near the edge of both test fields required a minimum contrast of 50% to achieve acceptable image CNR. The minimum contrast for large, centered objects ranged between 50% and 100%. Contrast-detail analysis using human detection of lower contrast limits provides fundamentally important information about the performance of reconstruction algorithms, and can be used to compare imaging performance of different systems.
©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)
Scott C. Davis, Brian W. Pogue, Hamid Dehghani, and Keith D. Paulsen "Contrast-detail analysis characterizing diffuse optical fluorescence tomography image reconstruction," Journal of Biomedical Optics 10(5), 050501 (1 September 2005). https://doi.org/10.1117/1.2114727
Published: 1 September 2005
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CITATIONS
Cited by 52 scholarly publications and 4 patents.
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KEYWORDS
Imaging systems

Atrial fibrillation

Image restoration

Signal to noise ratio

Fluorescence tomography

Luminescence

Reconstruction algorithms

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