Image analysis is one of the biggest challenges faced by today’s microscopists, especially in the fields of Medical and Life Science. In an age where high-throughput imaging is becoming more and more accessible, however, the question remains: What information to extract from the images, and how?
Machine learning techniques have shown huge potential for image segmentation and recognition and are often able to go a step beyond traditional image analysis methodologies. Pixel-based segmentation and classification, as well as deep neural networks (DNNs), are examples of popular machine learning tools taking advantage of deep learning methodologies to process and analyse images from different microscope modalities for highly specific and customizable applications.
In this webinar presented by ZEISS Australia/New Zealand and MetaSystems Asia, you will learn through real-world examples in research and routine diagnostics about the possibilities how machine learning is changing the game for microscopy through ZEISS Intellesis and MetaSystems DNN powered software solutions.
- Artificial Intelligence opens new possibilities for the automated processing and analysis of microscopic images, which were previously difficult or impossible
- ZEISS Intellesis and APEER
- MetaSystems DNN for high throughput microscopy