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arXiv · 2610.22840

Image Moment Estimation for Crowded Datasets

Andy Zhang·Oscar Mickelin·Amit Singer
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Abstract

Single-particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of reconstructing high-resolution three-dimensional (3D) structure of biological macromolecules from a set of noisy projection images taken at random viewing directions. The mathematical model for cryo-EM images typically assumes that each image contains exactly one particle, which is centered at the origin. However, many experimental datasets contain particle images which include multiple particles: one central particle and a few crowding particles. This deviation from the model leads to inaccurate estimation of image statistics, such as the low-order image moments. To account for this, we propose a method to estimate image moments while correcting for the effect of crowding particles. This method can be run directly from a set of cryo-EM micrographs with picked particles, and we demonstrate its efficacy on a wide array of synthetic data.

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Andy Zhang, Oscar Mickelin, Amit Singer. 2026-10-16. Image Moment Estimation for Crowded Datasets. https://arxiv.org/abs/2610.22840

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