Extended Data Fig. 11: Scaling predictions and CLEM auto-registration.
From: Whole-cell organelle segmentation in volume electron microscopy
a, Comparison of networks trained with 4 nm and simulated 8 nm raw data of all samples. Each data point represents the F1 score (test performance) on one of the four holdout blocks, similar to Fig. 2b. b, Qualitative comparison of automated and manual registration for the region marked with the dashed box in c. PALM images show ER (magenta) and mitochondria (green). Landmarks were placed at corresponding points in the ER light channel and ER predictions of the electron microscopy image that were not used for automatic registration. This unbiased measurement enables us to measure errors in an unbiased way, with respect to the true underlying transformation, not only the "part" of the transformation that can be inferred from the mitochondria membrane channel. White glyphs show human-human error (vertical) and human-automatic error (horizontal). Scale bar is 2 μm. c, A single slice of the Jacobian determinant map for the transformation registering electron microscopy to PALM for jrc_cos7-11. Red (blue) indicates local increase (decrease) in volume. Dotted area shows the approximate location of cells. Scale bar is 10 μm. d, Histogram of Jacobian determinant over the whole volume. e, Error map showing differences for automatic registrations using PALM or SIM as the target image. Dotted area shows the approximate location of cells. Scale bar is 10 μm. f, Histogram of PALM versus SIM errors over the area where a cell is present (white dotted line in e). All statistics from a single cell in a single dataset as specified.
