The following operations are part of the pipeline.
Pipeline operations layout
Input ROI
This operation allows to select the region of interest (ROI). ROI defines the dataset subarea that will be processed and analyzed by the pipeline.
Input ROI parameters
|
Parameter |
Description |
|
|---|---|---|
|
ROI |
Sets the processing and analysis target space. |
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|
– |
Current View |
The selected Z plane and the viewer area are processed. |
|
– |
Current Plane |
The selected Z plane is processed (XY). |
|
– |
Current Time Point |
The selected time point is processed (XYZ). |
|
– |
Current Image Set |
The complete dataset (XYZ and time) is processed. |
|
– |
Custom |
Allows to mix the previous methods. |
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Channels |
Sets the processing and analysis target channels. Selecting a single channel, all the operations in the pipeline will be forced to use it. |
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Scaling |
Sets the scaling of the dataset, which reduces it size. The measurements will not be modified by the scaling factor |
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Crop input data |
Sets the limitation of the data used for the calculation to only the cropped selection defined above. If this option is not selected, the entire image set is used for the calculation. |
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Additional Parameters
Additional settings for Input ROI expand, when you click in the operation.
|
Parameter |
Description |
|---|---|
|
Bounds |
Sets the analysis area edges. The whole XY bounds, the viewing area or a custom space can be applied. |
|
Planes |
Sets the analysis planes range. A single plane, a range of planes or the whole stack can be selected. |
|
Time Points |
Sets the analysis time points range. A single time pint, a range of time points or the whole movie can be selected. |
Machine Learning Segmenter
Automatic objects detection algorithm based on machine learning approach. The ML training (Nuclei and Membrane) was previously created.
In most cases, the default settings are suitable, and you don't need to change them. You can modify a few special parameters, related to the segments, by clicking the Operation menu > Segments.
Machine Learning Segmenter parameters
|
Parameter |
Description |
|
|---|---|---|
|
Training |
Shows the name of the Training that is loaded and some basic information below that. |
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Channels |
Sets the channels as input to this filter. The software will select the channels automatically based on the channels used for training. |
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Outputs |
Configure the outputs for this segmenter such as the output and classes name or the coloring of found segments. |
|
Object Feature Filter
The results of the Machine Learning Segmenter are filtered by volume to delete artifacts.
Object Feature Filter parameters
|
Parameter |
Description |
|
|---|---|---|
|
Input |
Sets the filter input. If more than one segment operation is present in your pipeline, the correct input source must be set. |
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Is of type |
Sets the type of filter which filters the objects based on the selected type. By default, it is set on Any for all object types. The list of available features is updated accordingly. |
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Filter selection |
Sets the function for the segmentation is performed. |
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Criterion Settings |
These parameters depend on the selection of the filter. |
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+ Add Filter |
Allows to add a Simple, Ratio or Tag filter criterions. |
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Store Objects
Store the detected segments (tag) in the active dataset.