Aivia Software
Cell Count - Cellpose
- Hung-yu Chang
- Chichou Huang
The Cell Count - Cellpose recipe in Aivia is a deep learning-based recipe designed to detect cells in 2D fluorescence microscopy images using Cellpose models. Unlike traditional image processing methods used in the original Cell Count recipe, this recipe requires fewer parameter adjustments, making it more user-friendly. The outputs of this recipe include detailed morphology and intensity measurements of the detected cells.
On this page:
Parameters and Presets
Parameters
Recipe parameters for Cell Count and their descriptions are summarized in the table below.
Preset Group | Parameter Name | Min Value | Max Value | Description |
|---|---|---|---|---|
Detection | Model Type | 1 | 3 | Specifies the model type that can be applied The available model types are the following:
cyto2 yields good results in most tested cases including nuclei and cytoplasm and is the recommended first step. |
Typical Cell Diameter | 0 | 1000 px2 or µm2 | Specifies the typical diameter of objects (e.g. cells / nuclei) on the image. This parameter is used for rescaling the image input to the Cellpose detection algorithm | |
Probability Threshold | 0 | 100 | The sensitivity of cell detection. Higher values mean a lesser number of detected cells. | |
Subset Filtering | Cell Diameter | 0 | 10,000 px2 or µm2 | Specifies the range of objects to be included in the analysis results based on the diameter of the detected cells |
Presets
There are two preset groups in the recipe: Detection and Subset Filtering. Each group has three pre-configured parameter groupings to help you get started on the analysis. The default preset values are in the sections to follow.
Detection
Parameter Name | Low | Medium | High |
|---|---|---|---|
Typical Cell Diameter | 5 | 20 | 80 |
Probability Threshold | 30 | 40 | 70 |
Subset Filtering
Parameter Name | Low | Medium | High |
|---|---|---|---|
Cell Diameter | 1 - 30 px2 or µm2 | 2 - 100 px2 or µm2 | 20 - 200 px2 or µm2 |
Tutorial (written steps)
Before beginning the tutorial, please download the Cell Count Demo image. For information on how to select presets or modify parameter values, please refer to the tutorial on how to use the Recipe Console.
Unzip the demo file and load the demo image, “CellCountDemo.tif,” into Aivia.
In the Recipe Console, click on the Recipe selection dropdown menu and select the Cell Count - Cellpose recipe.
Select the Low preset for the Detection group and the Low preset for the Subset Filtering group.
Click the Start button or press the
F4key on your keyboard to begin applying the recipe to the image.
The detected object outlines will be overlaid on the image.
Tutorial (videos)
Measurements
The Cell Count - Cellpose recipe generates morphological and intensity measurements for each detected cell as well as a count of the total number of cells on the image. You can add additional measurements to the analysis results by using the Measurement Tool in Aivia and explore measurement definitions on the Measurement Definitions page. The measurements generated by the recipe are in the table below.
Morphological | Intensity | Summary |
|---|---|---|
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