Aivia Software
Cell Count
- Hoyin Lai
- Aiden Maloney-Bertelli (Unlicensed)
- Casey McBride
- Lindsey Marshall
The Cell Count recipe in Aivia detects cells in fluorescence microscopy images. This recipe is designed for 2D data.
The recipe measures the morphology and intensity of the detected cells.
This recipe can be used for detection of any bright foreground objects against a dark background.
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 | Background Removal Factor (Remove Background only) | 0 | 100 | Adjusts the sensitivity of the background removal operation; a lower value will preserve larger objects and more background variations |
Contrast Threshold (Remove Background) Intensity Threshold (Skip Remove Background) | 0 | 255 (8-bit) 65,535 (16-bit) | Adjusts the detection sensitivity on the segmentation image; when Remove Background is selected, the threshold will be applied to the background-removed image; whereas when Skip Remove Background is selected, the threshold will be applied to the input image; a lower value will detect bigger and more objects | |
Fill Holes Size | 0 | 1,000,000 px2 or µm2 | Adjusts the maximum size threshold for filling in gaps inside a detected object; a lower value will preserve more holes in the detection | |
Smoothing Factor | 0 | 100 | Adjusts the amount of smoothing applied to the outline of the detected objects; a lower value will preserve more of the object's morphological features | |
Subset Filtering | Object Size | 0 | 1,000,000,000 px2 or µm2 | Specifies the range of objects to be included in the analysis results based on the areas of the detected objects |
Separation Factor (Cell Partition only) | 0 | 100 | Adjusts the sensitivity of the object separation operation; a lower value will preserve larger objects with multiple intensity peaks |
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 |
|---|---|---|---|
Background Removal Factor | 25 | 55 | 75 |
Contrast Threshold Intensity Threshold | 23 (8-bit) | 8 (8-bit) | 1 (8-bit) |
5,898 (16-bit) | 1,966 (16-bit) | 262 (16-bit) | |
Fill Holes Size | 10 px2 or µm2 | 25 px2 or µm2 | 50 px2 or µm2 |
Smoothing Factor | 4 | 4 | 4 |
Subset Filtering
Parameter Name | Small | Medium | Large |
|---|---|---|---|
Object Size | 1 - 250 px2 or µm2 | 50 - 1,000 px2 or µm2 | 150 - 6,000 px2 or µm2 |
Separation Factor | 50 | 70 | 85 |
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 recipe.
Select the High preset for the Detection group and the Small preset for the Subset Filtering group.
Click on the Show Advanced Interface icon to expand the Recipe Console and show parameter options for the recipe.
Modify the parameter values in the recipe as follows while leaving the other values intact:
Contrast Threshold: 90
Separation Factor: 81
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 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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