FLIMOLOGY

Meet FLIMOLOGY

Problem

Precise diagnosis of cancer relies on comprehensive interpretation of histology images by experienced pathologists. The preparation, digitalisation, and interpretation could be weeks, involving a massive amount of time and resources. Here, we propose the application of advanced deep learning technologies to full-spectral autofluorescence lifetime microscopy to significantly decrease the time and resources used for lung cancer diagnosis.

Solution

Autofluorescence lifetime images are stitched together for rapid visual recognition of lung cancer per the lifetime contrast across various emission wavelengths. The corresponding intensity images are translated to virtual histology images for precise recognition by pathologists.

Market

Hospitals, particularly those departments involving cancer diagnosis

Contact 

Qiang Wang

LinkedIn

Marta Vallejo

LinkedIn

Dorian Gouzou

LinkedIn

 

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