Ryan K. Hylton

This paper introduces a streamlined workflow for montage cryo-electron tomography that simplifies data acquisition and processing, enabling high-throughput, nanoscale-resolution imaging of biological samples.

The paper trains segmentation networks for cryo-ET data using synthetic and real data, showing that synthetic data with molecular diversity improves performance but real data is needed for generalization.