2003
DOI: 10.1016/s0021-9991(03)00150-5
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Coupled complex adjoint sensitivities for frequency-domain fluorescence tomography: theory and vectorized implementation

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Cited by 61 publications
(50 citation statements)
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“…The first-order Fréchet derivative of (or ) with respect to the fluorophore concentration at the EKF total concentration estimate at the th step is given by [31], [35], [36] (34)…”
Section: B Estimation Of Pharmacokinetic-rate Images By Extended Kalmentioning
confidence: 99%
See 1 more Smart Citation
“…The first-order Fréchet derivative of (or ) with respect to the fluorophore concentration at the EKF total concentration estimate at the th step is given by [31], [35], [36] (34)…”
Section: B Estimation Of Pharmacokinetic-rate Images By Extended Kalmentioning
confidence: 99%
“…where we define as the solution of (6) and (10), as the solution of (7) and (11), as the Green's function of (7) and (11), and as the solution of (6) and (10) where in (6) is replaced by given the EKF estimates of the fluorophore concentrations at different compartments at the th step [35]. In (34), the first integral results from the right-hand side of (7), while the second and third integrals originate from the dependence of and TABLE I EKF ALGORITHM FOR THE SIMULTANEOUS ESTIMATION OF FLUOROPHORE CONCENTRATION, PHARMACOKINETIC-RATE, AND VOLUME FRACTION IMAGES , respectively, on the unknown fluorophore absorption coefficient.…”
Section: B Estimation Of Pharmacokinetic-rate Images By Extended Kalmentioning
confidence: 99%
“…The fluorophore is elevated to an excited state and then decays to the ground state while releasing the energy. This creates fluorescence, which can be separated from the excitation light via interference filters [4]. The fluorescent photon has a longer wavelength than that of the excitation photon, resulting in a color shift.…”
Section: Introductionmentioning
confidence: 99%
“…The coupled diffusion equations for the case of fluorescence-enhanced imaging in the frequency domain are [104] [ ]…”
Section: Light Propagation In Biological Tissuesmentioning
confidence: 99%
“…[104] The Kalman filter is a linear state Bayesian estimator that is used in process control in order to estimate a state recursively, using the previous observations. The filter yields estimates of true measurement values and the corresponding calculated values by the following process: (i) predict a value, (ii) estimate the uncertainty of the predicted value, (iii) compute a weighted average of the predicted value and the measured value.…”
Section: Approximate Extended Kalman Filter (Aekf) Based Reconstructimentioning
confidence: 99%