List-mode detector scatter estimation method with potential for real-time implementation in high resolution PET imaging

A novel method for the estimation of list-mode detector scatter is proposed, which can in principle be implemented in real-time during raw PET data acquisition. The method displaces the event detection positions within the list-mode data (according to a scatter kernel) to create new events which are distributed according to the background detector scatter component. The approach operates in detector data space, and in effect uses shift-variant kernels when considered in parallel projection-data space. Point sources located at different positions in the field-of-view (FOV) were used to assess the method, along with extensive phantom experiments. List-mode data for an ¹⁸F rat bone scan (18 MBq) acquired with the quad-HIDAC PET scanner was reconstructed including the correction for the scatter and randoms background, demonstrating the method’s efficacy.