Optimal and Robust PET Data Sinogram Restoration Based on the Response of the System

We present an optimal and robust technique for the restoration of positron emission tomography (PET) data. It is based on an iterative deconvolution of Fourier Rebinned (FORE) sinograms employing the EM-ML algorithm regularized with MAP. The deconvolution kernel is related to the System Response Matrix (SRM) and the axial point spread function (PSF) caused by FORE. This method is able to deblur the acquired data without the introduction of additional noise and enhancing the quality (resolution, contrast) of the images reconstructed using FBP.

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