Robustness of Anatomically Guided Pixel-by-Pixel Algorithms for Partial Volume Effect Correction in Positron Emission Tomography

Abstract

Several algorithms have been proposed to improve positron emission tomography quantification by combining anatomical and functional information in a pixel-by-pixel correction scheme. The precision of these methods when applied to real data depends on the precision of the manifold correction steps, such as full-width half-maximum modeling, magnetic resonance imaging-positron emission tomography registration, tissue segmentation, or background activity estimation. A good understanding of the influence of these parameters thus is critical to the effective use of the algorithms. In the current article, the authors present a monodimensional model that allows a simple theoretical and experimental evaluation of correction imprecision. The authors then assess correction robustness in three dimensions with computer simulations, and evaluate the validity of regional SD as a correction performance criterion.