ERnet: a tool for the semantic segmentation and quantitative analysis of endoplasmic reticulum topology for video-rate super-resolution imaging
M. Lu, C. N. Christensen, J. M. Weber, T. Konno, N. F. Laubli, K. M. Scherer, E. Avezov, P. Lio, A. A. Lapkin, G. S. Kaminski Schierle, C. F. Kaminski
ERnet quantifies ER topology dynamics using video-rate super-resolution imaging and semantic segmentation, enabling analysis of ER morphology changes in response to genetic or metabolic perturbations.
bioRxiv · May 17, 2022 · PreprintBioengineering