  We develop a novel algorithm for large-scale holographic reconstruction of 3D
particle fields. Our method is based on a multiple-scattering beam propagation
method (BPM) combined with sparse regularization that enables recovering dense
3D particles of high refractive index contrast from a single hologram. We show
that the BPM-computed hologram generates intensity statistics closely matching
with the experimental measurements and provides up to 9$\times$ higher accuracy
than the single-scattering model. To solve the inverse problem, we devise a
computationally efficient algorithm, which reduces the computation time by two
orders of magnitude as compared to the state-of-the-art
multiple-scattering-based technique. We demonstrate superior reconstruction
accuracy in both simulations and experiments under different scattering
strengths. We show that the BPM reconstruction significantly outperforms the
single-scattering method in particular for deep imaging depths and high
particle densities.
