Aivia Software
Multiplexed Cell Detection Recipe
The Multiplexed Cell Detection recipe in Aivia is based on Cellpose, a generalist deep-learning based algorithm for cellular segmentation. This recipe is designed for 2D data.
The recipe detects cell membrane and nuclear membrane using multiple membrane marker channels and a single nucleus marker channel.
On this page:
Inputs and Outputs
Recipe inputs and outputs for Multiplexed Cell Detection and their descriptions are summarized in the table below.
| Name | Description |
|---|---|---|
Inputs | Deep Learning Model | (Optional) Select a deep learning model to apply before this recipe is applied |
Input Nucleus Image | Select the channel which contains the nuclei of cells in the image | |
Input Cell Membrane Images | Select the membrane marker channels to be used while detecting cells in this recipe | |
Outputs | Cells | Select the object set to which the results of the detection are outputted. Defaults to creating a new object set |
Parameters and Presets
Parameters
Recipe parameters for Multiplexed Cell Detection and their descriptions are summarized in the table below.
Preset Group | Parameter Name | Min Value | Max Value | Description |
|---|---|---|---|---|
Nucleus Detection | Nucleus Probability Threshold | 0 | 100 | Adjusts the sensitivity of nucleus detection. Higher values mean lesser number of detected cells |
Nucleus Diameter | 0 | 65535 px | Indicates the estimated diameter of typical cells | |
Min Nucleus Size | 0 | 65535 px2 or µm2 | Filters out and ignores nuclei of size smaller than this parameter | |
Nucleus Expansion Distance | 0 | 65535 | If no cell membrane is detected corresponding to a nucleus, the cell membrane is generated by expanding the nuclear membrane by a distance specified by this parameter | |
Cell Membrane Detection | Cell Membrane Probability Threshold | 0 | 100 | Adjusts the sensitivity of cell membrane detection. Higher values mean lesser number of detected cells membranes |
Presets
There are two preset groups in the recipe: Nucleus Detection and Cell Membrane Detection. 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.
Nucleus Detection
Parameter Name | Small | Medium | Large |
|---|---|---|---|
Nucleus Probability Threshold | 10 | 10 | 10 |
Nucleus Diameter | 10 px or µm | 20 px or µm | 30 px or µm |
Min Nucleus Size | 20 px2 or µm2 | 50 px2 or µm2 | 100 px2 or µm2 |
Nucleus Expansion Distance | 2 px or µm | 4 px or µm | 6 px or µm |
Cell Membrane Detection
Parameter Name | Low | Medium | High |
|---|---|---|---|
Cell Membrane Probability Threshold | 10 | 50 | 90 |
Tutorial (written steps)
Before beginning the tutorial, please download the Multiplexed Cell Detection 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, “MultiplexedCellDetectionDemo.aivia.tif,” into Aivia.
Set the calibration to 0.325 µm
In the Recipe Console, click on the Recipe selection dropdown menu and select the Multiplexed Cell Detection recipe.
Select the DAPI channel in the dropdown menu for Input Nucleus Image
Select following membrane marker channels in the dropdown menu for Input Cell Membrane Images:
CD3
CD45
CD4
CD8
GLUT1
HLA1
NAK
PCAD
Select the Small preset for the Nucleus Detection group and the Medium preset for the Cell Membrane Detection 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:
Nucleus Probability Threshold: 30
Nucleus Diameter: 5.5 µm
Min Nucleus Size: 15 µm2
Cell Membrane Probability Threshold: 40
Click the Start button or press the
F4key on your keyboard to begin applying the recipe to the image.
The detected nuclear and cell membrane outlines will be overlaid on the image.
Tutorial (videos)
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