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Suliana Manley's fluorescence microscope
Imagine you're a PhD student with a fluorescence microscope and a live bacterial sample
When the bacteria finally start to divide, you may give up food and rest, sitting uninterrupted in front of a microscope to acquire images
Alternatively, you may want to set up a microscope to take images
Another solution is to use artificial intelligence to detect precursors for bacterial division and use those precursors to automatically update the microscope's control software to take more photos of
Yes, EPFL biophysicists did find a way to automatically control microscopic detailed imaging of biological events with the help of artificial neural networks, while limiting stress
"Smart microscopes are a bit like self-driving cars
Manley and her colleagues first solved how to detect mitochondrial division, which is harder than bacteria, which is unpredictable because it occurs very frequently and can occur almost anywhere
When both contraction and protein levels are high, the microscope switches to high-speed imaging to capture many detailed images
With this intelligent fluorescence microscope, the scientists showed that they could observe samples
Manley explains: "The potential of smart microscopy includes measuring what
Scientists use the control framework as an open source plug-in
Event-driven acquisition for content-enriched microscopy
