Manual segmentation of microscopy images is very time consuming, wastes valuable researcher time, and introduces human bias. In contrast, classical intensity-based approaches for image segmentation do not always work with complex images, due to factors such as low signal-to-noise ratios and uneven staining.
Artificial Intelligence (AI) has gained significant prominence in bioimage analysis as it assists in minimizing bias, standardizing the pipelines, and expediting results.
This webinar showcases an AI-driven image analysis pipeline that any researcher can develop and execute without the need to code. You will also learn about the development of a customized-trained model using deep learning and how to use it to power and scale an end-to-end image analysis pipeline.
Our experts discuss why you need AI in your image analysis and will showcase a real use case in the Zeiss digital eco-system, with the arivis Cloud and arivis Pro solutions.

Key Learnings:

In this webinar, you will discover:

• The benefits of advanced AI-driven image analysis methods
• How to get faster, more robust, and reproducible image segmentation
• How to develop and execute an AI-driven image analysis pipeline without coding skills
• The applications of deep learning approaches for 3D image analysis