Using Linear Time-Invariant System Theory to Estimate Kinetic Parameters Directly from Projection Me - Nuclear Science, IEEE Transactions on
نویسنده
چکیده
It is common practice to estimate kinetic parameters from dynamically acquired tomographic data by first reconstructing a dynamic sequence of three-dimensional reconstructions and then fitting the parameters to time activity curves generated from the time-varying reconstructed images. However, in SPECT, the pharmaceutical distribution can change during the acquisition of a complete tomographic data set, which can bias the estimated kinetic parameters. It is hypothesized that more accurate estimates of the kinetic parameters can be obtained by fitting to the projection measurements instead of the reconstructed time sequence. Estimation from projections requires the knowledge of their relationship between the tissue regions of interest or voxels with particular kinetic parameters and the projection measurements, which results in a complicated nonlinear estimation problem with a series of exponential factors with multiplicative coefficients. A technique is presented in this paper where the exponential decay parameters are estimated separately using linear timeinvariant system theory. Once the exponential factors are known, the coefficients of the exponentials can be estimated using linear estimation techniques. Computer simulations demonstrate that estimation of the kinetic parameters directly from the projections is more accurate than the estimation from the reconstructed images.
منابع مشابه
Time-Invariant State Feedback Control Laws for a Special Form of Underactuated Nonlinear Systems Using Linear State Bisection
Linear state bisection is introduced as a new method to find time-invariant state feedback control laws for a special form of underactuated nonlinear systems. The specialty of the systems considered is that every unactuated state should be coupled with at least two directly actuated states. The basic idea is based on bisecting actuated states and using linear combinations with adjustable parame...
متن کاملBlind Intensity Estimation from Shot-Noise Data - Signal Processing, IEEE Transactions on
The estimation of the intensity function of an inhomogeneous Poisson process is considered when the observable data consists of sampled shot noise that results from passing the Poisson process through an unknown linear time-invariant system. The proposed method consists of first estimating a histogram of the underlying point process. The estimated histogram is used to construct a kernel estimat...
متن کاملGlobal exponential stability of recurrent neural networks for synthesizing linear feedback control systems via pole assignment
Global exponential stability is the most desirable stability property of recurrent neural networks. The paper presents new results for recurrent neural networks applied to online computation of feedback gains of linear time-invariant multivariable systems via pole assignment. The theoretical analysis focuses on the global exponential stability, convergence rates, and selection of design paramet...
متن کاملOn the stabilization of discrete-time linear time-varying systems
This note considers feedback stabilization of discrete-time linear time-varying systems. An operator-theoretic formulation of time-varying systems is used which allows the development to follow closely the linear time-invariant case. Using this framework, an extended Lyapunov stability result is derived. This leads to a direct proof of a feedback stabilization scheme due to Cheng without the us...
متن کاملReliable Decentralized Stabilization of Linear Systems - Automatic Control, IEEE Transactions on
Reliable stabilization of linear time-invariant multiinput/multi-output plants is considered using a two-channel decentralized controller configuration. Necessary and sufficient conditions are obtained for existence of reliable controllers that maintain stability under the possible failure of either one of the two controllers. All decentralized controllers that achieve reliable stabilization ar...
متن کامل