Counting the Number of Objects in a Ring around the Nucleus

This example is similar to Measuring Mean Fluorescence Intensity on a Ring around the primary Object and also uses the same data. This example shows how to count the number of objects on a ring that is associated with the main object, e.g. the cell nucleus. The images are taken from AF568 stained nuclei. The mitochondria are stained with AF488. The channel of the nuclei is used for image segmentation. The ZOI-segmentation method attributes a zone of influence (ZOI) and a ring to each detected nucleus. This area is used as a search range to detect subobjects, in this case the mitochondria.

Step 1: Classes

You have set up the image analysis setting with the method ZOI (Zones of Influence) and have opened the Image Analysis Wizard, see Creating a New Image Analysis Setting

In the Classes step, select Ring or Ring Element and click Add Subclass to extend the predefined set of classes with a subclass of the Ring Element.
Another class below the Ring Element is added.
Give this class a meaningful name, e.g. Mitochondria/Mitochondrion.
The cell nuclei (primary objects) are stained with AF568 (red channel), therefore you need to select this channel to segment the cell nuclei. Select Primary Object and for Channel select AF568.
Click on Mitochondrion and select AF488 in the Channel field.
The mitochondria are stained with AF488, therefore you need to use this channel for image segmentation.

Step 2: Frame

For more information, see Step 2: Frame.

Step 3: Automatic Segmentation

For more information, see Step 3: Automatic Segmentation.

Additionally, you need to set the segmentation parameters for the object Mitochondrion. Choose suitable parameters to segment the objects.
You have detected the mitochondria on the ring.

Step 4: Region Filter

For more information, see Step 3: Automatic Segmentation.

Step 5: Features

You can define individual measurement features for each class. The measurement features defined for one class you can copy to the other classes via Copy to all.

Select the class for which you want to define measurement features, and click Edit. From the list of features on the right you can add features to the selected features list on the left.
These features are automatically defined for every object during image analysis. All classes have ID of the parent and ID as default features. This allows you to later to group the associated parameters from the excel lists, if necessary.
The class Ring additionally has Area and Count as default parameters.
In this example, we count the number of objects (the number of mitochondria fragments) within each ring. To attribute the number of mitochondria fragments to the Primary Object, select Mitochondria and click Edit.
The Feature Selection dialog opens.
In the parameter list on the right, select the feature Count. In the Copy drop-down menu, click .
This measurement feature is copied to the corresponding Primary Object.

Step 6: Preview Result

In this step you see a preliminary result of the image analysis.

Click on the different objects in the Analysis tab to get the preliminary measurement result for all objects.
Select the Primary Object to get a list with preliminary measurement results with the features ID of the parent, ID, Area, and Ring Mitochondria Counts. Note that the results are preliminary and only include the part of the image you see in the viewport.
The result of the image analysis shows Ring Mitochondria Counts as a feature of Primary Object.
In the table, click on column Ring Mitochondria Counts to sort the entries in increasing or decreasing order.
Click on Finish to save the analysis settings and to close the wizard.

You can now run the analysis as described in Measuring Mean Fluorescence Intensity on a Ring around the Primary Object.