The symmetries of image formation by scattering. II. Applications

TL;DR

This paper introduces a graph-theoretic manifold-embedding method leveraging symmetries in scattering image formation to extract structural and temporal information from low-signal datasets, enabling 3D reconstruction and dynamic system analysis.

Contribution

It presents a novel, physically-based, noise-robust computational approach for analyzing scattering data, including 3D structure recovery and dynamic evolution from ultra-low-signal images.

Findings

Successful 3D structure recovery from X-ray diffraction and cryo-EM images.

Achieved 12-fold dose reduction in cryo-EM imaging.

Sequenced random sightings into high-quality movies of dynamic systems.

Abstract

We show that the symmetries of image formation by scattering enable graph-theoretic manifold-embedding techniques to extract structural and timing information from simulated and experimental snapshots at extremely low signal. The approach constitutes a physically-based, computationally efficient, and noise-robust route to analyzing the large and varied datasets generated by existing and emerging methods for studying structure and dynamics by scattering. We demonstrate three-dimensional structure recovery from X-ray diffraction and cryo-electron microscope image snapshots of unknown orientation, the latter at 12 times lower dose than currently in use. We also show that ultra-low-signal, random sightings of dynamically evolving systems can be sequenced into high quality movies to reveal their evolution. Our approach offers a route to recovering timing information in time-resolved experiments, and extracting 3D movies from two-dimensional random sightings of dynamic systems.