The objective of this work is to estimate and simulate organ uptake variability and correlations using measured data from the FastSPECT II Single Photon Emission Computed Tomography (SPECT) imaging system. We will investigate various methods that attempt to determine organ-uptake within a set of organs in a digital phantom; these methods include Region-of-Interest, Gauss-Markov, Wiener, and Reconstruction Estimation algorithms. In addition to the estimators, we will also test whether moving the phantom with respect to the imaging system and gathering multiple images from different positions will improve the performance of our estimators. The variations and correlations in the object will be modeled using Gaussian distributions with first and second-order statistics known exactly. We will present a mathematical formulation of this model, in a texture-free context, as well as some results on image-quality assessment. The object model will be the MOBY digital mouse phantom; the 4-D MOBY Mouse Model is a digital phantom developed by Paul Segars (Segars et al., 2004), which provides a useful digital model for nuclear-medicine and CT imaging. |