SOURCE-LINKED INTELLIGENCE

Smart, Event-Based Microscopy for Cell Biology

CORDIS · observation · Publication date unknown

dowed with user-friendly, unsupervised decision-making algorithms, transforming microscopes into fully responsive and automated measurement devices. Indeed, we are at a moment when smart systems and artificial intelligence are being used everywhere, including in laboratories to improve the functioning of many (scientific), however outdated preprogrammed microscopy workflows are still being routinely implemented. The ability to employ real-time image analysis to inform, optimize and adjust the settings of ongoing image acquisitions would be a game changer for studying complex, dynamic cellular processes. To address this issue, we have developed a pilot software, CyberSco.Py, which enables the possibility to conduct image analysis in real time (using deep learning) to trigger modifications in the acquisition settings thus alleviating the need for manual input and supervision. This allows for the implementation of novel classes of experiments that cannot be achieved with current solutions. Within the context of this PoC, CyberSco.Py will be developed into a user-friendly softwar

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recordType

award

status

SIGNED

region

EU

value

150000

unit

EUR