Nonlinear conjugate gradient method for spectral tomosynthesis

Image reconstruction in spectral digital breast tomosynthesis (DBT) requires solving a large-scale nonlinear inverse problem. Most numerical approaches on real data used a simplified linear (and hence incorrect) mathematical model to reduce the computational costs. The aim of this paper is to consider the use of a nonlinear conjugate gradient method for very large-scale nonlinear least squares problems, and apply it to spectral DBT. Numerical experiments on 3-dimensional phantom images illustrate the effectiveness and efficiency of the proposed scheme.