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In a number of applications, positron emission tomography (PET) requires two or more scans to observe and even quantify changes in function (e.g. tissue metabolism, or receptor binding potentials). Conventionally the raw datasets are reconstructed into images independently, allowing no sharing of information. Kernelised EM (KEM) is a recently proposed PET reconstruction method that utilises one or...
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...
A variety of approaches have been proposed to reduce the variance in reconstructed PET images. In this work, we assess the effect of different combinations of variance reduction techniques on the quality of reconstructed images. These methods include MLEM with early termination, MLEM with post-smoothing, MAPEM and MLEM with inclusion of a convolution matrix prior to the system matrix. Different combinations...
Positron emission tomography (PET) measurements with time-of-flight (TOF) information are often very sparse. As a result, direct reconstruction from raw list-mode data is an attractive strategy for dealing with the large dimension spanned by the measurements. However, even though sparse datasets are more efficiently processed in list mode than as sinograms, list-mode reconstruction remains computationally...
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