Image segmentation is usually the biggest challenge in image analysis as segmentation lays the foundation for subsequent image analysis steps like data extraction and quantification. Conventional threshold-based image-segmentation methods frequently require a specialised workflow using a combination of digital filters and tools. Moreover, there are datasets where threshold-based methods struggle or fail to generate meaningful results (e.g., images with low signal to noise ratio).
Machine learning, on the other hand, offers even non-experts the possibility to create robust and reproducible segmentation results easily. Moreover, machine-learning methods often yield good results with challenging images.
The software module ZEN Intellesis enables easy and precise segmentation of multidimensional images using supervised machine learning. ZEN Intellesis can be trained to identify objects within an image automatically. Through an easy to use, GUI based training interface, ZEN Intellesis enables non-experts to easily segment complex data sets without needing knowledge of machine learning. An end-to-end image analysis workflow from ‘Images to data’ can be created using Intellesis as the segmentation tool.
This webinar will introduce the basics of machine learning and provide an overview of ZEN Intellesis as well as a few of its applications.
Date: Tuesday, April 19, 2020 2:30 PM - 3:30 PM SGT
Speaker: Manoj Mathew (ZEISS)