Segment cells

[haesleinhuepf]

I would like to segment cells in an image with membrane staining. Can I do this with nsbatwm?

git-bob comment

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Yes, you can use the nsbatwm library to segment cells in an image with membrane staining. You can apply the seeded watershed segmentation method, which is well-suited for this task. Here is an example of how you might use it:

import napari_segment_blobs_and_things_with_membranes as nsbatwm

# Assuming 'membrane_image' is your input image with membrane staining
# and 'nuclei_labels' is a labeled image of nuclei

segmented_cells = nsbatwm.seeded_watershed(membrane_image, nuclei_labels)

This function uses the labeled nuclei as seeds to segment the cells based on the membrane staining in the image. Adjust your input variables accordingly.

[haesleinhuepf]

What if I didn't have a label image for the nuclei?

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If you don't have a labeled image for the nuclei, you can first create one using the Voronoi-Otsu labeling, which is suitable for detecting blob-like structures such as nuclei. Here's how you might do that:

import napari_segment_blobs_and_things_with_membranes as nsbatwm

### Assuming 'nuclei_image' is your input image of nuclei

nuclei_labels = nsbatwm.voronoi_otsu_labeling(nuclei_image, spot_sigma=4, outline_sigma=1)

### Now you can proceed with the seeded watershed segmentation

segmented_cells = nsbatwm.seeded_watershed(membrane_image, nuclei_labels)

[haesleinhuepf]

I also don't have an image showing the nuclei. I only have one image showing the membranes. What function can process it to segment cells?

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^{This message was generated by git-bob (version: 0.6.6, model: gpt-4o-2024-08-06, Run details), an experimental AI-based assistant. It can make mistakes and has limitations. Check its messages carefully.}

import napari_segment_blobs_and_things_with_membranes as nsbatwm

##### When you only have an image showing membranes, you can use local minima as seeds
##### for watershed segmentation. Here's how you can process it:

segmented_cells = nsbatwm.local_minima_seeded_watershed(membrane_image, spot_sigma=10, outline_sigma=2)