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    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.

    Inputs and Outputs

    Recipe inputs and outputs for Multiplexed Cell Detection and their descriptions are summarized in the table below.

     

    Name

    Description

     

    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

    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.

    1. Unzip the demo file and load the demo image, “MultiplexedCellDetectionDemo.aivia.tif,” into Aivia.

    2. Set the calibration to 0.325 µm

    3. In the Recipe Console, click on the Recipe selection dropdown menu and select the Multiplexed Cell Detection recipe.

    4. Select the DAPI channel in the dropdown menu for Input Nucleus Image

    5. Select following membrane marker channels in the dropdown menu for Input Cell Membrane Images:

      • CD3

      • CD45

      • CD4

      • CD8

      • GLUT1

      • HLA1

      • NAK

      • PCAD

    6. Select the Small preset for the Nucleus Detection group and the Medium preset for the Cell Membrane Detection group.

    7. Click on the Show Advanced Interface icon to expand the Recipe Console and show parameter options for the recipe.

    8. 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

    9. Click the Start button or press the F4 key on your keyboard to begin applying the recipe to the image.

    The detected nuclear and cell membrane outlines will be overlaid on the image.

    Multiplexed Cell Detection tutorial results
    Results at 100% scaling

     

     

    Tutorial (videos)

     

     

     

     

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