Motion Detection in Diffraction Tomography by Common Circle Methods

TL;DR

This paper introduces novel methods for detecting rigid motions in optical diffraction tomography by identifying common circles in Fourier data, enabling full reconstruction of object orientations.

Contribution

It adapts common line techniques from cryo-EM to optical diffraction tomography, allowing for motion detection and orientation reconstruction using common circles.

Findings

Methods successfully detect rotations and translations in simulated data.

Reformulation as common line methods enables full orientation reconstruction.

Numerical examples demonstrate effective motion detection in diffraction data.

Abstract

The method of common lines is a well-established reconstruction technique in cryogenic electron microscopy (cryo-EM), which can be used to extract the relative orientations of an object given tomographic projection images from different directions. In this paper, we deal with an analogous problem in optical diffraction tomography. Based on the Fourier diffraction theorem, we show that rigid motions of the object, i.e., rotations and translations, can be determined by detecting common circles in the Fourier-transformed data. We introduce two methods to identify common circles. The first one is motivated by the common line approach for projection images and detects the relative orientation by parameterizing the common circles in the two images. The second one assumes a smooth motion over time and calculates the angular velocity of the rotational motion via an infinitesimal version of the common circle method. Interestingly, using the stereographic projection, both methods can be reformulated as common line methods, but these lines are, in contrast to those used in cryo-EM, not confined to pass through the origin and allow for a full reconstruction of the relative orientations. Numerical proof-of-the-concept examples demonstrate the performance of our reconstruction methods.