Digital breast tomosynthesis (DBT) provides a pseudo-3D
reconstruction which addresses the limitation of superimposition of dense
fibro-glandular tissue associated with conventional mammography. Reg-
istration of temporal DBT volumes searches for the optimum deforma-
tion to transform two observed images of the same object into a common
reference frame. This aligns the two images via minimising an objective
function that calculates the similarity between the two datasets.
In this paper, we present a novel algorithm which combines recon-
struction of a pair of temporal DBT acquisitions with their simultaneous
registration. We approach this nonlinear inverse problem using a generic
unconstrained optimisation scheme. To evaluate the performance of our
method we use 2D and 3D software phantoms and demonstrate that this
simultaneous approach has comparable results to performing these tasks
sequentially or iteratively w.r.t both the reconstruction fidelity and the
registration accuracy.