Note
Go to the end to download the full example code.
Electron Microscopy#
Applying the cellsam_pipeline to segment electron microscopy images of bacteria.
This dataset comprises an electron microscope image of a bacterial biofilm. This FOV is downsampled from data provided by the Newman Lab at Caltech; image credit Mark Ladinsky @ the Caltech CryoEM facility.

(512, 512)
/home/administrator/envs/cs-13-dev/lib/python3.13/site-packages/cellSAM/sam_inference.py:351: UserWarning: Low IOU threshold, ignoring mask.
warnings.warn("Low IOU threshold, ignoring mask.")
/home/administrator/repos/cellSAM/examples/plot_electron_microscopy.py:40: FutureWarning: `napari.view_image` is deprecated and will be removed in napari 0.7.0.
Use `viewer = napari.Viewer(); viewer.add_image(...)` instead.
nim = napari.view_image(img, name="EMimage");
import zarr
import skimage
import napari
from cellSAM import cellsam_pipeline
# NOTE: data is stored with zarr_format 3
assert int(zarr.__version__[0]) > 2
# Access EM image
store = zarr.storage.FsspecStore.from_url(
"s3://cellsam-gallery-sample-data/sample-data.zarr",
storage_options={"anon": True},
read_only=True,
)
z = zarr.open_group(store=store, mode="r")
# Load EM image into local memory
# Limit to lower-right quadrant to reduce CI computation load
tilesize = 512
img = z["biofilm_electron_microscopy"][tilesize:, tilesize:]
print(img.shape)
# Segment
mask = cellsam_pipeline(img, use_wsi=False)
# Visualize
nim = napari.view_image(img, name="EMimage");
nim.add_labels(mask, name="Cellsam segmentation");
if __name__ == "__main__":
napari.run()
Total running time of the script: (0 minutes 7.595 seconds)