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Reliable estimation of membrane curvature for cryo-electron tomography

Fig 10

Algorithms and parameters comparison using a small cER membrane feature from cryo-ET.

Surface of a cER membrane region with maximum base radius ∼10 nm (from the same tomogram of a yeast cell as the cER in Fig 11) was generated using the compartment segmentation. Panels (A-B) show relative frequency histograms of κ1 estimated by (A) AVV or (B) SSVV using rh = 2, 5, 10, 15 and 20 nm. Panels (C-D) show visualizations of the estimated κ1 and κ2 (color scale was set to the value range of [-0.1, 0.1] nm-1 in both panels) and the corresponding principal directions (black arrows, sampled for every forth triangle) by (C) AVV or (D) SSVV using rh = 10 nm (scale bar: 20 nm, applies for both panels).

Fig 10

doi: https://doi.org/10.1371/journal.pcbi.1007962.g010