3D Multiplexed Cell Detection Recipe

Inputs

Deep Learning Model

Select a deep learning model to apply before this recipe is applied

Input Image(s)

Select the cell membrane or nuclear membrane marker channel(s) to be used while detecting cells in this recipe

Outputs

Cells

Select the object set to which the results of the detection are outputted. Both 3D meshes and 2D slices of detected cells are created. Defaults to creating a new object set.

Detection

Model Type

1

3

Specifies the model type that can be applied

The available model types are the following:
1: ‘cyto’; 2: ‘nuclei’, 3: ‘cyto2’

 cyto2 yields good results in most tested cases including nuclei and cytoplasm and is the recommended first step.

Typical Cell Diameter

0

1,000

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

Adjusts the sensitivity of cell/nucleus detection. The threshold is applied to the probability map shown in the Detection preview. Higher values mean lesser number of detected cells or nuclei

Image Smoothing Filter Size

(excluding Skip Smooth Image only)

0

100

Specifies the diameter of the filter that is used to smooth the input channel before further processing

The available smoothing types are the following:

• Skip Smoothing - recommended setting for Cellpose as the first step before trying additional smoothing below

• Average Filter Smoothing applies an average filter with a filter kernel width and height specified by the value of the Image Smoothing Filter Size. The averaging filter is applied in 2D to each Z-stack of the input channel(s).

• Gaussian Filter Smoothing applies a Gaussian filter with a filter kernel width and height specified by the value of the Image Smoothing Filter Size. The Gaussian filter is applied in 2D to each Z-stack of the input channel(s).

• Median Filter Smoothing applies a median filter with a filter kernel width and height specified by the value of the Image Smoothing Filter Size. The Median filter is applied in 2D to each Z-stack of the input channel(s).

Partition

Cell Diameter

0

10,000

Specifies the range of detected cells or nuclei to keep based on their diameters

Mesh Smoothing Factor

1

10

Adjusts the amount of smoothing applied to the surface reconstructions of the detected Cells; a lower value will generate surfaces with greater similarity to the input image

Z-Stack Area Overlap Threshold

(For the “Use standard method” option)

0.0

1.0

Specifies the intersection over union (IoU) threshold to determine whether to merge masks across Z stacks.

• A higher threshold will result in stricter merging criteria, potentially leading to more detected cells but introducing the risk of splitting a cell into partial cells.

• A lower threshold may result in more merged cells, potentially capturing more detail but introducing the risk of merging unrelated structures.

Max Z-Stack Displacement

(For the “Use flow-based method” option)

0

1,000

Specifies the displacement limit between mask centers to determine whether to merge masks across Z stacks.

• A lower value will result in stricter merging criteria, potentially leading to more detected cells but introducing the risk of splitting a cell into partial cells.

• A higher value may result in more merged cells, potentially capturing more detail but introducing the risk of merging unrelated structures.