Year: 2026
Type: article
Abstract: A single-particle cryo-electron microscopy (cryo-EM) measurement, called a micrograph, consists of multiple two-dimensional tomographic projections of a three-dimensional (3-D) molecular structure at unknown locations, taken under unknown viewing directions. All existing cryo-EM algorithmic pipelines first locate and extract the projection images, and then reconstruct the structure from the extracted images. However, if the molecular structure is small, the signal-to-noise ratio (SNR) of the data is very low, making it challenging to accurately detect projection images within the micrograph. Consequently, all standard techniques fail in low-SNR regimes. To recover molecular structures from measurements of low SNR, and in particular small molecular structures, we devise an approximate expectation-maximization algorithm to estimate the 3-D structure directly from the micrograph, bypassing the need to locate the projection images. We corroborate our computational scheme with numerical experiments and present successful structure recoveries from simulated noisy measurements.
Source: Inverse Problems and Imaging
DOI: 10.3934/ipi.2026033
Authors: Shay Kreymer, Amit Singer, Tamir Bendory
Institutions: Tel Aviv University, Princeton University
Language: English
Subfield: Structural Biology
Domain: Life Sciences
Open Access status: hybrid
Awards: G1523888516, G1801485972, NSF-BSF: Theory, algorithms, and applications of estimation over groups, G36446433, Reconstruction of heterogeneous and small macromolecules by cyro-EM, G4688056592, G5103908366, G5729145195, G7026105293, NSF-BSF: Modern Techniques for Signal Reconstruction from Moments, G7416518505, G7489706817
OpenAlex ID: W7153981587