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28 July 2017 Spectrally constrained L1-norm improves quantitative accuracy of diffuse optical tomography
Wenqi Lu, Iain B. Styles
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Proceedings Volume 10412, Diffuse Optical Spectroscopy and Imaging VI; 1041211 (2017) https://doi.org/10.1117/12.2285996
Event: European Conferences on Biomedical Optics, 2017, Munich, Germany
Abstract
We consider L1-regularization of spectrally constrained DOT. Three popular algorithms are investigated: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM) and fast iterative shrinkage-thresholding algorithm (FISTA). We evaluate different regularizers and algorithms on a 3D simulated multi-spectral example.
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Wenqi Lu and Iain B. Styles "Spectrally constrained L1-norm improves quantitative accuracy of diffuse optical tomography", Proc. SPIE 10412, Diffuse Optical Spectroscopy and Imaging VI, 1041211 (28 July 2017); https://doi.org/10.1117/12.2285996
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KEYWORDS
Diffuse optical tomography
Inverse problems
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