Wavelet based Multiresolution Expectation Maximization reconstruction algorithm for Positron Emission Tomography (PET)

نویسنده

  • Amar Raheja
چکیده

Maximum Likelihood estimation based Expectation Maximization(EM) reconstruction algorithm [ 11 has been shown to provide good quality reconstruction for PET. Our previous work [2,3] introduced multigrid concept for PET image reconstruction using EM. The multiresolution EM (MREM) algorithm is an attempt to improve the EM based estimation through an effective use of multi-resolution grids in both image-reconstruction and detector spaces. The algorithm begins iterating at the coarsest grid level using tube data that has been re-organized (re-binned) at the coarsest detector level. It switches both the grid and detector levels simultaneously until the finest detector and grid resolution are reached. This algorithm incorporates a wavelet decomposition based transition criterion for switching grid levels and a wavelet spline based interpolation method for projecting the intermediate reconstruction from a specific grid level to the next finer grid.

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Pii: S0895-6111(00)00035-5

Maximum Likelihood (ML) estimation based Expectation Maximization (EM) [IEEE Trans Med Imag, MI-1 (2) (1982) 113] reconstruction algorithm has shown to provide good quality reconstruction for positron emission tomography (PET). Our previous work [IEEE Trans Med Imag, 7(4) (1988) 273; Proc IEEE EMBS Conf, 20(2/6) (1998) 759] introduced the multigrid (MG) and multiresolution (MR) concept for PET ...

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تاریخ انتشار 2004