Cellpose-Based Segmenter
This operation detects automatically cells using pretrained cellpose models.
Cellpose-based Segmenter parameters
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Parameter |
Description |
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Channel |
Sets the channel where the cells will be segmented. |
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Optional channel |
Sets a second optional channel (e.g., nuclei channel) to support the segmentation. |
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Cellpose model |
Sets a pre-trained cellpose model from the list of built-in models. |
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CP |
Sets a model, which is mainly trained on fluorescent cell images . |
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CPx |
Sets a model, which is trained on wide variety of images. |
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Cyto |
Sets a cytoplasm model, which is trained on one channel cell images (if the image had a nuclear channel). |
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Cyto2 |
Sets a cytoplasm model, which is trained on two channels cell images (if the image had a nuclear channel). |
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Nuclei |
Sets a model, which is trained on two-channel images. The first channel is the channel to segment, and the second channel is always set to an array of zeros. |
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Load external model |
Sets a custom model, which allows you to load and run your trained Cellpose models or any pre-trained Cellpose models not included in the operation. |
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Cell diameter |
Sets value of the diameter of your cells. Alternatively, use the Measure |
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Min area |
Sets the reference objects diameter. Select a value to filter out the objects with smaller area, volume, or diameter. |
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tool to determine it.Additional Parameters
Additional settings for Cellpose-based Segmenter expand when you click 
in the operation.
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Parameter |
Description |
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Mask threshold |
Sets the cell probability threshold between -6 and +6 to determine what is a cell and what is background. |
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Mask quality threshold |
Sets the maximum allowable errors (mean square error) of the flows for each detected cell. The filter range is between 0 and 1 to exclude masks with lower quality values. |
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Smooth Cellpose model results |
Sets the Gaussian smoothing process, to refine the output, reduce noise and potentially improve the overall performance of your cell detection application. |
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Normalization percentile |
Sets the normalization range. The default values are 1% to 99%, where everything below the lower threshold and everything above the upper threshold is mapped out as outliers. Note:Increase the range if you have data with big background areas and very little area of actual bright signal |