The general process of doing image analysis in arivis is fairly simple. We use the Analysis Panel to create Pipelines. Those pipelines are built from individual operations that work with each other to extract the information we need. Pipelines can then easily be re-used with other images as needed, including in batch mode to streamline the process.

Of course, the process we described here is only the basic principle of pipeline:

• Enhance images if needed
• Use images to segment objects
• Use the segmented objects to extract useful information
• Save the results

The full breadth of what can be done in a pipeline cannot be covered here. The inclusion of Machine Learning and Deep Learning makes it possible to segment objects that were previously impossible to segment, and the pipeline tools allow us to extract all sorts of useful information from these segmentation. Please check our pipeline examples, to find out more about the types of information arivis can extract from images, and to learn more about how individual operations work.

Finally, again since our Knowledge Base and sample pipelines couldn't hope to fully cover what can be achieved in a pipeline, don't hesitate to get in touch with your local ZEISS representative.