  List-mode data is increasingly being uesd in SPECT and PET imaging, among
other imaging modalities. However, there are still many imaging designs that
effectively bin list-mode data before image reconstruction or other estimation
tasks are performed. Intuitively, the binning operation should result in a loss
of information. In this work we show that this is true for Fisher information
and provide a computational method for quantifying the information loss. In the
end we find that the information loss depends on three factors. The first
factor is related to the smoothness of the mean data function for the list-mode
data. The second factor is the actual object being imaged. Finally, the third
factor is the binning scheme in relation to the other two factors.
