The essential reason to use imaging techniques in the life sciences is the generation of data to answer biological questions. This aim is in general accomplished by using a combination of image acquisition and advanced image analysis.
Conventional imaging follows the constant interaction of an operator, searching for suitable objects or regions of interest (ROIs) on the sample, with the microscopy system and making appropriate optimal acquisition settings to decisively scan these ROIs. Due to the nature of such a manually defined experimental workflow, only a manageable number of ROIs can be precisely localized, and the acquisition of ROIs requires a lot of time.
The rare event detection workflow performed by applying Autonomous Microscopy powered by Aivia works completely autonomous after the setup at the beginning of the experiment. As soon as the experiment is started, no human intervention is required from a low-resolution pre-scan to the detection of rare events and the acquisition and storage of the high-resolution 3D images.
The clear benefit is the high speed of this process and the large number of detected rare events during the experiment
A new AI-based detection workflow for confocal microscopy from Leica automates the detection of rare events. It follows what the user has defined as the objects of interest that will trigger the rare event scan. Users benefit from the potential to discover more by automatically detecting up to 90% of rare events during an experiment. By focusing on the data that matter during the acquisition process itself, time to result can be reduced by up to 70%. The Aivia-powered workflow reduces time spent at the microscope by up to 75%, leading to increased productivity to do more.
"Autonomous Microscopy powered by Aivia brings the power of Artificial Intelligence to everyday experimental environments in an easy-to-use way," says James O'Brien, Vice President of Life Sciences and Applied Microscopy at Leica Microsystems. "Researchers can now establish confocal microscopy workflows that address advanced experiments and biological questions that would be impossible or very laborious without automated procedures. This solution gives them outstanding new options to obtain results that answer their research questions."
The rare event detection workflow is based on the interaction of two components available on a STELLARIS confocal system. Often, overview scans of the biological sample are analyzed. If the Aivia AI-based image analysis software detects indications of a rare event, the positions are sent back to the controlling software of STELLARIS which is called Navigator Expert. The positions of the identified events are automatically scanned at high resolution and in three dimensions based on the user's defined settings.
With Autonomous Microscopy powered by Aivia, operator interaction is limited to the initial setup. Objects are detected much faster and more accurately. The same settings can be applied for other experiments to ensure consistency. Because only objects of interest are identified and captured, data acquisition and final analysis time is significantly reduced. This exclusivity also means an extreme saving of storage space.
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