SOURCE-LINKED INTELLIGENCE

Multiphoton imaging with computational specificity

CORDIS · observation · Publication date unknown

Multiphoton imaging with computational specificity Digital staining based on machine learning models can provide cellular specificity to label-free optical imaging. This concept is particularly interesting for in vivo applications in fundamental research of auto-immune diseases as well as for future clinical translations. In this project “MICS – Multiphoton imaging with computational specificity”, I will develop and implement computational specificity for label-free multiphoton microscopy (MPM) using artificial intelligence (AI). The direct outcome of this project will be two AI modules to perform (i) automated classification of mucosal inflammation based on 3D images from colon tissue and (ii) digital staining of un-stained immune cells. This integration of computational specificity to label-free multiphoton microscopy will allow direct investigation of global tissue alteration as well as specific immune cell localization during inflammatory tissue remodelling.

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recordType

award

status

SIGNED

region

EU

value

192125.76

unit

EUR