ArticleJournal of biomedical optics2018
Parameterized level-set based pharmacokinetic fluorescence optical tomography using the regularized Gauss-Newton filter.
Article in Journal of biomedical optics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Shape-optimized Model-based Reconstruction Algorithm for Radiacoustic Imaging.Applied physics letters · 2026Article
- Parameterized level-set based pharmacokinetic fluorescence optical tomography using the regularized Gauss-Newton filter.Journal of biomedical optics · 2018Article
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3 authors.
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Abstract
Pharmacokinetic tomography is emerging as an important methodology for detecting abnormalities in tissue based upon spatially varying estimation of the pharmacokinetic rates governing the leakage of an injected fluorophore between blood plasma and tissue. We present a shape-based reconstruction framework of a compartment-model based formulation of this dynamic fluorescent optical tomography problem to solve for the pharmacokinetic rates and concentrations of the fluorophore from time-varying log intensity measurements of the optical signal. The compartment-model based state variable model is set up in a radial basis function parameterized level set setting. The state (concentrations) and (pharmacokinetic) parameter estimation problem is solved with an iteratively regularized Gauss-Newton filter in a trust-region framework. Reconstructions obtained using this scheme for noisy data obtained from cancer mimicking numerical phantoms of near/sub-cm sizes show a good localization of the affected regions and reasonable estimates of the pharmacokinetic rates and concentration curves.
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