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Motion during PET data acquisition is either introduced by design (e.g. couch wobble, detector rotation, bed translations) or through motion of the subject (e.g. rigid body motion of the head, respiratory motion). At present such effects are generally considered very differently in PET imaging, with intentional motion regarded as beneficial for enriching data sampling whilst subject motion is regarded...
Tomographic reconstruction from PET data is an ill-posed problem that requires regularization. Recently, Daubechies et al. proposed an l1 regularization of the wavelet coefficients that can be optimized using iterative thresholding schemes. In this paper, we extend this approach for the reconstruction of dynamic (spatio-temporal) PET data. Instead of using classical wavelets in the temporal dimension,...
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