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Reconstruction of dynamic PET data using spatio-temporal wavelet l(1) regularization
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| Abstract |
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| Tomographic reconstruction from PET data is an W-posed problem that requires regularization. Recently, Daubechies et al. [1] proposed an l(1) 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, we introduce exponential-spline wavelets that are specially tailored to model time activity curves (TACs) in PET. We show the usefulness of spatio-temporal regularization and the superior performance of E-spline wavelets over conventional Battle-Lemarie wavelets for a 1-D TAC fitting experiment and a tomographic reconstruction experiment. | | |
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English
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Proceedings of the ... Annual international conference of the IEEE engineering in medicine and biology society. - New York (N.Y.) | |
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New York (N.Y.) : IEEE, 2007
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1094-687X
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(2007), p. 6540-6543
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| ISI |
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000253467005165
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