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Regularization of iterative reconstruction for fully dynamic PET has often been achieved implicitly by estimating coefficients relating to temporal basis functions, such as data-derived temporal basis functions, wavelet temporal basis functions, or compartmental model based temporal basis functions (direct kinetic parameter estimation). In this work, we propose and evaluate a method for anatomy-guided...
Image reconstruction from low-count positron emission tomography (PET) projection data is challenging because the inverse problem is ill-posed. Prior information can be used to improve image quality. Inspired by the kernel methods in machine learning, this paper proposes a kernel based method that models PET image intensity in each pixel as a function of a set of features obtained from prior information...
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