Uncertainty quantification in dynamic image reconstruction with applications to cryo-em

Here, we propose combining empirical Bayes modeling with recent ad-vances in Markov chain Monte Carlo filters for hidden Markov models. In doing so, we address long-standing problems in the reconstruction of 3D images, with uncertainty quantification, from noisy 2D pixels in cryogenic electron microscopy and other applications, such as brain network development in infants.