Evaluating Deep Learning Architectures for Actin Filament Segmentation Under Varying Noise Conditions in Simulated Cryo-ET Tomograms

This work evaluates deep-learning architectures for segmenting actin filament networks in simulated cryo-electron tomograms, with emphasis on robustness across varying noise conditions.