A bootstrap approach for analyzing the statistical properties of SPECT and PET images

Abstract

We describe a non-parametric bootstrap method to estimate the statistical properties of single photon emission computed tomography (SPECT) and positron emission tomography (PET) images, whatever the type of noise in the projections and the reconstruction algorithm. Using analytical simulations and real PET data, this method is shown to accurately predict the statistical distribution, hence the variance, of reconstructed pixel values for both linear and nonlinear reconstruction algorithms.