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Accelerating Neuron Image Analysis with Automation

The ability to examine complex neural processes relies on the accurate reconstruction of neuronal networks at scale. Most data extraction methods in neuroscience research are time-consuming and…
Separation of cells based on their tracking status: A colourised binary mask of a time-lapse microscopy field of view of medium confluency with individual cells highlighted as survivors if they can be tracked since the initial movie frame (cyan), incomers if they migrated into the field of view throughout the movie (yellow) or mistracks if an error occurred in the automated trajectory reconstruction (red).

Tracking Single Cells Using Deep Learning

AI-based solutions continue to gain ground in the field of microscopy. From automated object classification to virtual staining, machine and deep learning technologies are powering scientific…
Analysis of anatomy and axon orientation of an adult mouse brain tissue with QLIPP.

Learning the Cellular Architecture from its Optical Properties

In the last 3 years, microscopists have started to use "AI based" solutions for a wide range of applications, including image acquisition optimization (smart microscopy), object classification, image…
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