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A hybrid scatter correction for 3D PET based on an estimation of the distribution of unscattered coincidences: implementation on the ECAT EXACT HR+
Authors:Ferreira N C  Trébossen R  Lartizien C  Brulon V  Merceron P  Bendriem B
Affiliation:Service Hospitalier Frédéric Joliot, Orsay, France.
Abstract:We implemented a hybrid scatter-correction method for 3D PET that combines two scatter-correction methods in a complementary way. The implemented scheme uses a method based on the discrimination of the energy of events (the estimation of trues method (ETM)) and an auxiliary method (the single scatter simulation method (SSSI) or the convolution-subtraction method (CONV)) in an attempt to increase the accuracy of the correction over a wider range of acquisitions. The ETM takes into account the scatter from outside the field-of-view (FOV), which is not estimated with the auxiliary method. On the other hand, the auxiliary method accounts for events that have scattered with small angles, which have an energy that cannot be discriminated from that of unscattered events using the ETM. The ETM uses the data acquired in an upper energy window above the photopeak (550-650 keV) to obtain a noisy estimate of the unscattered events in the standard window (350-650 keV). Our implementation uses the auxiliary method to correct the residual scatter in the upper window. After appropriate scaling, the upper window data are subtracted from the total coincidences acquired in the standard window, resulting in the final scatter estimate, after smoothing. In this work we compare the hybrid method with the corrections used by default in the 2D and 3D modes of the ECAT EXACT HR+ using phantom measurements. Generally, the contrast was better with the hybrid method, although the relative errors of quantification were similar. We conclude that hybrid techniques such as the one implemented in this work can provide an accurate, general-purpose and practical way to correct the scatter in 3D PET, taking into account the scatter from outside the FOV.
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