MAXIMUM LIKELIHOOD RECONSTRUCTION FOR TOMOSYNTHESIS

摘要

In this paper, we present a maximum likelihood (ML) algorithm for tomosynthesis that reconstructs a 3D radiation attenuation coefficient map from a set of radiographies taken from various view angles. The ML algorithm is developed based on the Poisson model of the two dimensional radiography. The ML reconstruction yields better image quality with fewer artifacts than the wildly used filtered backprojection (FBP) reconstruction. Finally, we show representative results on simulated data.