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Accurate system modeling in tomographic image reconstruction has been shown to reduce the spatial variance of resolution and improve quantitative accuracy. System modeling can be improved through analytic calculations, Monte Carlo simulations, and physical measurements. The purpose of this work is to improve clinical fully-3-D reconstruction without(More)
A sampled-data filtering framework is presented for cardiac motion recovery from periodic medical image sequences. Cardiac dynamics is a continuously evolving physiological process, whereas the imaging data can provide only sampled measurements at discrete time instants. Stochastic multi-frame filtering frameworks are constructed to couple the continuous(More)
PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic(More)
Dynamic PET reconstruction is a challenging issue due to the spatio-temporal nature and the complexity of the data. Conventional frame-by-frame approaches fail to explore the temporal information of dynamic PET data, and may lead to inaccurate results due to the low SNR of data. Due to the ill-conditioning of image reconstruction, proper prior knowledge(More)
A continuous-discrete filtering strategy is proposed for cardiac kinematics estimation from periodic medical image sequences. Stochastic multi-frame filtering frameworks are constructed to deal with the parameter uncertainty of the biomechanical constraining model and the noisy nature of the imaging data coordinately. For the system with continuous dynamics(More)
A sampled-data H∞ filtering strategy is proposed for the estimation of cardiac kinematic functions from periodic medical image sequences. Given the biomechanics-based myocardial dynamics, stochastic multi-frame filtering frameworks are constructed to deal with the parameter uncertainty of the biomechanical constraining model and the noisy nature of the(More)
The electrochemically reductive dechlorination of 2,4-dichlorophenol (2,4-DCP) in aqueous solution on palladium/polymeric pyrrole-cetyl trimethyl ammonium bromide/foam-nickel electrode (Pd/PPy-CTAB/foam-Ni electrode) was investigated in this paper. Pd/PPy-CTAB/foam-Ni electrode was prepared and characterized by cyclic voltammetry (CV), scanning electron(More)
A sampled-data H<sub>infin</sub> filtering strategy is proposed for cardiac kinematics estimation from periodic medical image sequences. Stochastic multi-frame filtering frameworks are constructed to deal with the parameter uncertainty of the biomechanical constraining model and the noisy nature of the imaging data in a coordinated fashion. As robustness is(More)