Study of multispectral convolution scatter correction in high resolution PET

PET images acquired with a high resolution scanner based on arrays of small discrete detectors are obtained at the cost of low sensitivity and increased detector scatter. It has been postulated that these limitations can be overcome by using enlarged discrimination windows to include more low energy events and by developing more efficient energy-dependent methods to correct for scatter. In this work, we investigate one such method based on the frame-by-frame scatter correction of multispectral data. Images acquired in the conventional, broad and multispectral window modes were processed by the stationary and nonstationary consecutive convolution scatter correction methods. Broad and multispectral window acquisition with a low energy threshold of 129 keV improved system sensitivity by up to 75% relative to conventional window with a ~350 keV threshold. The degradation of image quality due to the added scatter events can almost be fully recovered by the subtraction-restoration scatter correction. The multispectral method was found to be more sensitive to the nonstationarity of scatter and its performance was not as good as that of the broad window. It is concluded that new scatter degradation models and correction methods need to be established to fully take advantage of multispectral data