Bio Applications Wizard

In this wizard you define the settings for your Bio Applications. In this wizard you have your image, the settings for the Bio Applications, basic view options as in the 2D view and an additional Legends window. This window displays information about the individual regions in the image and can be toggled on and off with the right click menu entry Regions Legend.

The options and parameters shown here in the wizard are, for the most part, Bio Application specific. The following parameters are generally available:

Parameter	Description
Name	Sets the name for the class/objects that is analyzed by this Bio Application.
Channel	Selects the image channel for the analysis.
Color	Selects a color for the resulting masks. Note: Use a different color than the channel color to be able to differentiate between mask and measurement signal.
Finish	Saves the changes and closes the wizard.
Cancel	Closes the wizard without saving the changes.

Cell Counting Specific Settings

Parameter		Description
Segm. Method		Selects the method for segmentation.
–	Automatic	Uses threshold values that are determined automatically from the histogram based on the Otsu method. For all possible threshold values, the Otsu method calculates the variance of intensities on each side of the respective threshold. It minimizes the sum of the variances for the background and the foreground.
–	Manual	Sets the threshold manually by clicking on the regions in the image that you want to segment, or by using the Threshold control displayed below.
–	Semantic	Uses semantic segmentation based on machine learning to automatically segment (fluorescently labeled) cell nuclei. This requires an installation of the 3rd party Python Tools during the installation of ZEN.
–	Instance	Uses an AI model for instance segmentation to automatically segment (fluorescently labeled) cell nuclei. The AI models for instance segmentation need the software Docker Desktop to run.
AI Model		Only visible if Semantic or Instance is selected. Selects the model for segmentation from a dropdown which includes your own trained and imported networks as well as a default neural network for the segmentation of fluorescently labeled nuclei. Note that you can only use models trained on a single channel.
AI Model Version		Only visible if Instance is selected. Selects the model version you want to use.
Model Class		Only visible if Semantic or Instance is selected. Selects the model class used for segmentation.
Min. Confidence		Only visible if Semantic or Instance is selected. Sets the minimum confidence in % for the prediction of every object.
Threshold		Only visible if Manual is selected. Sets the threshold for the pixel intensity used by the segmentation. For an RGB image you can set the threshold for each color channel individually.
–	Low	Defines the lowest pixel intensity considered for the segmentation.
–	High	Defines the highest pixel intensity considered for segmentation.
–		Undoes the last change.
Pick to Segment		Only visible if Manual is selected.
–	+	Enables you to expand the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
–	-	Enables you to reduce the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
Histogram		Only visible if Manual is selected. In the histogram you can change the lower and upper threshold value by dragging the lower or upper adjustment handle or shift the entire highlighted area between the lower and upper threshold value.
BG Subtraction
–	On	Applies a rolling ball background subtraction to the image.
–	Off	Applies no background subtraction to the image.
Area		Sets the lowest and highest value for the area of the objects. For more information, see the list of Measurement Features.
Circularity		Sets the lowest and highest value for the roundness of the objects. For more information, see the list of Measurement Features.
+ Pick to Include		Enables you to expand the values employed for the region filters (area and circularity) by clicking on objects in the image.

Confluency Specific Settings

Parameter		Description
Segmentation Type		Selects the type of segmentation.
–	Manual	Uses a manual threshold by clicking on the regions in the image that you want to segment, or by using the Threshold control displayed below.
–	Semantic	Uses machine learning to automatically segment the structures. The use of AI-segmentation requires an installation of the 3rd party Python Tools during the installation of ZEN.
Segm. Area		Only visible if Manual is selected. Selects which area is segmented.
–	Structure	Segments the structure(s) in the image.
–	Background	Segments only the background of the image.
Threshold		Only visible if Manual is selected. Sets the threshold for the variance calculation. If Structure is selected, it sets the threshold for the minimum variance of the structures in your image, i.e. all areas which have a variance value higher than the specified threshold will be segmented. If Background is selected, it sets the threshold for the maximum variance of the background, i.e. all areas which have a variance value lower than the specified threshold will be segmented.
Kernel Size		Only visible if Manual is selected. Sets the kernel size to calculate the variance value of one pixel with the neighboring pixels.
AI Model		Only visible if AI-based is selected. Selects the model for segmentation from a dropdown which includes your own trained and imported networks.
Model Class		Only visible if AI-based is selected. Selects the model class used for segmentation.
Min. Confidence		Only visible if AI-based is selected. Sets the minimum confidence in % for the prediction of every object.
Min. Object Size		Sets the minimum size in pixel that an object must have to be segmented.
Fill all Holes
–	On	Fills all holes in the segmented objects irrespective of their size.
–	Off	Fills holes in the segmented objects only if they are smaller than the specified Min. Hole Area.
Min. Hole Size		Sets the minimum area in pixel for the holes in the detected objects. The input is synchronized with Min. Object Size, which cannot be smaller than Min. Hole Size.

Gene- and Protein Expression Specific Settings

For Gene- and Protein Expression you have to specify settings for the nuclei segmentation as well as for quantification of the gene expression in the respective step.

Parameter		Description
Segm. Method		Only visible in the Nuclei step. Selects the method for segmentation.
–	Automatic	Uses threshold values that are determined automatically from the histogram based on the Otsu method. For all possible threshold values, the Otsu method calculates the variance of intensities on each side of the respective threshold. It minimizes the sum of the variances for the background and the foreground.
–	Manual	Sets the threshold manually by clicking on the regions in the image that you want to segment, or by using the Threshold control displayed below.
–	Semantic	Uses semantic segmentation based on machine learning to automatically segment (fluorescently labeled) cell nuclei. This requires an installation of the 3rd party Python Tools during the installation of ZEN.
–	Instance	Uses an AI model for instance segmentation to automatically segment (fluorescently labeled) cell nuclei. The AI models for instance segmentation need the software Docker Desktop to run.
AI Model		Only visible if Semantic or Instance is selected. Selects the model for segmentation from a dropdown which includes your own trained and imported networks as well as a default neural network for the segmentation of (fluorescently labeled) nuclei. Note that you can only use models trained on a single channel.
AI Model Version		Only visible if Instance is selected. Selects the model version you want to use.
Model Class		Only visible if Semantic or Instance is selected. Selects the model class used for segmentation.
Min. Confidence		Only visible if Semantic or Instance is selected. Sets the minimum confidence in % for the prediction of every object.
Threshold		Only visible in the Nuclei step and if Manual is selected. Sets the threshold for the pixel intensity used by the segmentation. For an RGB image you can set the threshold for each color channel individually.
–	Low	Defines the lowest pixel intensity considered for the segmentation.
–	High	Defines the highest pixel intensity considered for segmentation.
–		Undoes the last change.
Pick to Segment		Only visible in the Nuclei step and if Manual is selected.
–	+	Enables you to expand the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
–	-	Enables you to reduce the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
Histogram		Only visible in the Nuclei step and if Manual is selected. In the histogram you can change the lower and upper threshold value by dragging the lower or upper adjustment handle or shift the entire highlighted area between the lower and upper threshold value.
BG Subtraction
–	On	Applies a rolling ball background subtraction to the image.
–	Off	Applies no background subtraction to the image.
Area		Only available in the Nuclei step. Sets the lowest and highest value for the area of the objects. For more information, see the list of Measurement Features.
Circularity		Only available in the Nuclei step. Sets the lowest and highest value for the roundness of the objects. For more information, see the list of Measurement Features.
Pick to Include +		Enables you to expand the values employed for the region filters (area and circularity) and the mean intensity in the second step by clicking on objects in the image.
Ring Distance		Only available in the Nuclei step. Sets the distance between the inner border of the ring and the border of the segmented nuclei.
Ring Width		Only available in the Nuclei step. Sets the width of the ring where the gene expression is measured.
Intensity Mean		Only available in the Gene- and Protein Expression step. Sets the lowest and highest value for the mean intensity measurement of the selected channel. For more information, see the list of Measurement Features. If the mean intensity of a cell falls into that defined range, it is considered as a positive cell.

Automated Spot Detection Specific Settings

For Automated Spot Detection you have to specify settings for the nuclei segmentation as well as the spot detection itself in the respective step.

Parameter		Description
Segm. Method		Selects the method for segmentation.
–	Automatic	Uses threshold values that are determined automatically from the histogram based on the Otsu method. For all possible threshold values, the Otsu method calculates the variance of intensities on each side of the respective threshold. It minimizes the sum of the variances for the background and the foreground.
–	Manual	Sets the threshold manually by clicking on the regions in the image that you want to segment, or by using the Threshold control displayed below.
–	Semantic	Uses semantic segmentation based on machine learning to automatically segment (fluorescently labeled) cell nuclei. This requires an installation of the 3rd party Python Tools during the installation of ZEN.
–	Instance	Uses an AI model for instance segmentation to automatically segment (fluorescently labeled) cell nuclei. The AI models for instance segmentation need the software Docker Desktop to run.
AI Model		Only visible if Semantic or Instance is selected. Selects the model for segmentation from a dropdown which includes your own trained and imported networks as well as a default neural network for the segmentation of fluorescently labeled nuclei. Note that you can only use models trained on a single channel.
AI Model Version		Only visible if Instance is selected. Selects the model version you want to use.
Model Class		Only visible if Semantic or Instance is selected. Selects the model class used for segmentation.
Min. Confidence		Only visible if Semantic or Instance is selected. Sets the minimum confidence in % for the prediction of every object.
Threshold		Only visible if Manual is selected. Sets the threshold for the pixel intensity used by the segmentation. For an RGB image you can set the threshold for each color channel individually.
–	Low	Defines the lowest pixel intensity considered for the segmentation.
–	High	Defines the highest pixel intensity considered for segmentation.
–		Undoes the last change.
Pick to Segment		Only visible if Manual is selected.
–	+	Enables you to expand the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
–	-	Enables you to reduce the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
Histogram		Only visible if Manual is selected. In the histogram you can change the lower and upper threshold value by dragging the lower or upper adjustment handle or shift the entire highlighted area between the lower and upper threshold value.
BG Subtraction
–	On	Applies a rolling ball background subtraction to the image.
–	Off	Applies no background subtraction to the image.
Area		Sets the lowest and highest value for the area of the objects. For more information, see the list of Measurement Features.
Circularity		Sets the lowest and highest value for the roundness of the objects. For more information, see the list of Measurement Features.
+ Pick to Include		Enables you to expand the values employed for the region filters (area and circularity) by clicking on objects in the image.
Ring Distance		Only available in the Nuclei step. Sets the distance between the inner border of the ring and the border of the segmented nuclei.
Ring Width		Only available in the Nuclei step. Sets the width of the ring where the spots are detected.

Translocation Specific Settings

Parameter		Description
Segm. Method		Selects the method for segmentation.
–	Automatic	Uses threshold values that are determined automatically from the histogram based on the Otsu method. For all possible threshold values, the Otsu method calculates the variance of intensities on each side of the respective threshold. It minimizes the sum of the variances for the background and the foreground.
–	Manual	Sets the threshold manually by clicking on the regions in the image that you want to segment, or by using the Threshold control displayed below.
–	Semantic	Uses semantic segmentation based on machine learning to automatically segment (fluorescently labeled) cell nuclei. This requires an installation of the 3rd party Python Tools during the installation of ZEN.
–	Instance	Uses an AI model for instance segmentation to automatically segment (fluorescently labeled) cell nuclei. The AI models for instance segmentation need the software Docker Desktop to run.
AI Model		Only visible if Semantic or Instance is selected. Selects the model for segmentation from a dropdown which includes your own trained and imported networks as well as a default neural network for the segmentation of (fluorescently labeled) nuclei. Note that you can only use models trained on a single channel.
AI Model Version		Only visible if Instance is selected. Selects the model version you want to use.
Model Class		Only visible if Semantic or Instance is selected. Selects the model class used for segmentation.
Min. Confidence		Only visible if Semantic or Instance is selected. Sets the minimum confidence in % for the prediction of every object.
Threshold		Only visible if Manual is selected. Sets the threshold for the pixel intensity used by the segmentation. For an RGB image you can set the threshold for each color channel individually.
–	Low	Defines the lowest pixel intensity considered for the segmentation.
–	High	Defines the highest pixel intensity considered for segmentation.
–		Undoes the last change.
Pick to Segment		Only visible if Manual is selected.
–	+	Enables you to expand the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
–	-	Enables you to reduce the currently segmented regions by the gray values/colors of the objects subsequently clicked on.
Histogram		Only visible if Manual is selected. In the histogram you can change the lower and upper threshold value by dragging the lower or upper adjustment handle or shift the entire highlighted area between the lower and upper threshold value.
BG Subtraction		Only visible if Automatic or Manual is selected.
–	On	Applies a rolling ball background subtraction to the image.
–	Off	Applies no background subtraction to the image.
Area		Sets the lowest and highest value for the area of the objects. For more information, see the list of Measurement Features.
Circularity		Sets the lowest and highest value for the roundness of the objects. For more information, see the list of Measurement Features.
Pick to Include +		Enables you to expand the values employed for the region filters (area and circularity) and the mean intensity in the second step by clicking on objects in the image.
Translocation Channel		Selects the channel to quantify translocation.
Ring Distance		Sets the distance between the inner border of the ring and the border of the segmented nuclei.
Ring Width		Sets the width of the ring where the translocation is measured.

Bio Applications Wizard

See also

Cell Counting Specific Settings

See also

Confluency Specific Settings

See also

Gene- and Protein Expression Specific Settings

See also

Automated Spot Detection Specific Settings

See also

Translocation Specific Settings

See also

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