Motion Detection in Diffraction Tomography by Common Circle Methods
Michael Quellmalz, Peter Elbau, Otmar Scherzer, Gabriele Steidl
TL;DR
The paper tackles the challenge of reconstructing unknown rigid motion (rotations $R_t$ and translations ${\boldsymbol d}_t$) of a scattering object in optical diffraction tomography under the Born approximation. It develops two motion-detection approaches inspired by cryo-EM: a direct common circle method that uses intersections of hemispheres to recover relative rotations, and an infinitesimal variant that estimates angular velocity $\boldsymbol{\omega}_t$ and integrates to obtain $R_t$, leveraging the Fourier diffraction theorem. Translations are recovered from the complex measurements by exploiting phase information along common circles (and their duals), with a least-squares and phase-unwrapping framework. Numerical experiments on realistic phantoms demonstrate that joint motion estimation and subsequent 3D reconstruction are feasible, even with moving rotation axes and translations, highlighting the method’s potential for diffraction tomography with optically trapped samples. The work establishes a rigorous motion-reconstruction framework, connecting common-circle geometry, stereographic projection, and higher-order constraints to enable phase-aware motion estimation in diffraction-based imaging.
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.
