  Resolution level and reconstruction quality in nano-computed tomography
(nano-CT) are in part limited by the stability of microscopes, because the
magnitude of mechanical vibrations during scanning becomes comparable to the
imaging resolution, and the ability of the samples to resist beam damage during
data acquisition. In such cases, there is no incentive in recovering the sample
state at different time steps like in time-resolved reconstruction methods, but
instead the goal is to retrieve a single reconstruction at the highest possible
spatial resolution and without any imaging artifacts. Here we propose a joint
solver for imaging samples at the nanoscale with projection alignment,
unwarping and regularization. Projection data consistency is regulated by dense
optical flow estimated by Farneback's algorithm, leading to sharp sample
reconstructions with less artifacts. Synthetic data tests show robustness of
the method to Poisson and low-frequency background noise. Applicability of the
method is demonstrated on two large-scale nano-imaging experimental data sets.
