3-D Tomosynthesis Image Reconstruction Using Total Variation

Abstract

In tomosynthesis imaging, out-of-focus slice blur problem arises due to incomplete sampling problem. Several approaches have been proposed to deal with this problem. Algebraic reconstruction technique (ART) is one of the most commonly used methods. Total variation (TV) minimization has recently been applied to improve performance of the classical approaches. Though it is able to provide improved results, its sensitivity to the regularization parameter is still an important issue. Former studies addressed largely 2-D tomosynthesis image reconstruction problem. In this study, a 3-D phantom model was used to understand the effect of total variation minimization on a 3-D image reconstruction problem. The significance of selecting an appropriate regularization parameter of TV not addressed in the prior studies was also investigated by means of comparing root mean square error (RMSE) and contrast to noise ratio (CNR) values.