1. Select the Channel.
   Note: You can select a single or multiple channels.
2. To select the features that are used for the machine learning, select from the Feature set dropdown list.
3. To set up the Custom feature, click Feature .
4. The Feature dialog is displayed.
   
   Note: You can select all or a combination of the available features and resolutions. You can apply the features dimensions to 2D or 3D.
4. To disable a feature totally, click on a feature row header.
5. To disable a resolution totally, click on a resolution column header.
6. Click OK.
7. Select the Classes by which to classify the pixels in the image.
   Note: By default, the Background class and the Class 1 object class is added.
8. To add classes, click + Add Class
9. To rename the class, double-click on the class header.
10. Click Brush tool.
11. The cursor switched to a brush.
    
11. To select regions representative for the classes, drag the brush on the image.
    Note: Annotate several small segments rather than large few. Try to cover all the different structure conditions (e.g., intensity, texture, etc.) present in your training images. Don’t overlay annotation to the background and other structures.
12. Each annotation is shown under the related class.
    
12. To delete an annotation, right-click on it and click Remove selected object.
13. To check the quality of the training , click Preview tabs.
    
14. The preview shows which pixels will be segmented.
    
14. Click Train.
15. To export the training for further usage, click Panel menu > Export.
    
16. To open the pipeline with the Machine Learning Segmenter operation, click Open in Pipeline.