A Non-Parametric Approach to Particle Picking in All Frames

Evgeny Hershkovitch Neiterman
Ayelet Heimowitz
Gil Ben-Artzi
School of Computer Science, Ariel University
Department of Electronics and Electrical Engineering, Ariel University

Journal of Structural Biology

Paper

Code



Highlights

  • A novel, non-parametric method for detecting tomographic projections across all movie frames, using temporal consistency.
  • Independent of motion correction, CTF estimation, and initial reconstruction.
  • Results demonstrate reduced outlier rate and accurate particle localization comparable to existing approaches throughout the entire movie sequence.

Abstract

Single-particle cryo-electron microscopy (cryo-EM) has significantly advanced macromolecular structure reconstruction. However, a key limitation is the conventional reliance on micrographs obtained by motion correction and averaging, which inherently loses the richness of information contained within each frame of the original movie. The future of cryo-EM reconstruction ideally involves harnessing the raw signal from every frame to unlock potentially higher quality structures. In this paper, we present a first essential step toward this paradigm shift, that is, a novel, non-parametric method for detecting tomographic projections across all movie frames, using temporal consistency. Our method is inspired by Structure-from-Motion (SfM), and independent of motion correction, CTF estimation, and initial reconstruction. Our experimental results demonstrate reduced outlier rate and accurate particle localization comparable to existing approaches throughout the entire movie sequence.


Method



Our approach to recovering individual tomographic projections involves a two-step process that aims to discard the incorrect weak hypotheses, that is, the incorrect projection positions. To this end, we use the temporal consistency of the positions of genuine tomographic projections across frames, allowing for small translations only.


Results


Visualization of 3D reconstructions on the EMPIAR-10028 dataset. Left is the original coordinates, right is ours.