Self-consistent automatic retrieval of single cell rotation enables highly reliable holo-tomographic flow cytometry

Abstract

Holo-Tomographic Flow Cytometry (HTFC) is a powerful, label-free imaging technique that allows obtaining three-dimensional (3D) refractive index (RI) tomograms of individual flowing and rotating cells. Determining the unknown orientation of moving cells is crucial for tomographic reconstruction. There is significant potential to enhance previous methods by increasing accuracy, achieving full automation, and reducing the dependence on a priori information. Here, we present a novel self-consistent method for the accurate and automatic retrieval of unknown rotations of single cells. The proposed method retrieves the sequence of rotation angles by an iterative reprojection-based optimization algorithm of the reconstructed 3D RI tomogram. The experimental results demonstrate that the method proposed in this work achieves full automation and superior accuracy, thus surpassing the existing techniques. This advancement markedly improves the scalability of HTFC, enabling automatic and highly reliable analysis of single cells.