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1 March 2011Toward robust high resolution fluorescence tomography: a
hybrid row-action edge preserving regularization
Depth-resolved localization and quantification of fluorescence distribution in tissue, called Fluorescence Molecular
Tomography (FMT), is highly ill-conditioned as depth information should be extracted from limited number of
surface measurements. Inverse solvers resort to regularization algorithms that penalize Euclidean norm of the
solution to overcome ill-posedness. While these regularization algorithms offer good accuracy, their smoothing
effects result in continuous distributions which lack high-frequency edge-type features of the actual fluorescence
distribution and hence limit the resolution offered by FMT. We propose an algorithm that penalizes the total
variation (TV) norm of the solution to preserve sharp transitions and high-frequency components in the
reconstructed fluorescence map while overcoming ill-posedness. The hybrid algorithm is composed of two levels: 1)
An Algebraic Reconstruction Technique (ART), performed on FMT data for fast recovery of a smooth solution that
serves as an initial guess for the iterative TV regularization, 2) A time marching TV regularization algorithm,
inspired by the Rudin-Osher-Fatemi TV image restoration, performed on the initial guess to further enhance the
resolution and accuracy of the reconstruction. The performance of the proposed method in resolving fluorescent
tubes inserted in a liquid tissue phantom imaged by a non-contact CW trans-illumination FMT system is studied and
compared to conventional regularization schemes. It is observed that the proposed method performs better in
resolving fluorescence inclusions at higher depths.
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Ali Behrooz, Hao-Min Zhou, Ali A. Eftekhar, Ali Adibi, "Toward robust high resolution fluorescence tomography: a hybrid row-action edge preserving regularization," Proc. SPIE 7896, Optical Tomography and Spectroscopy of Tissue IX, 78961E (1 March 2011); https://doi.org/10.1117/12.874305