Title
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Reconstruction of dynamic PET data using spatio-temporal wavelet l(1) regularization
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Author
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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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Language
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English
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Source (journal)
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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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Publication
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New York (N.Y.)
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IEEE
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2007
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ISSN
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1094-687X
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Volume/pages
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(2007)
, p. 6540-6543
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ISI
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000253467005165
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