Combined ultraviolet confocal reflectance and autofluorescence microscopy for generating virtual sectioned histology in freshly resected thick tissues

Developing imaging modalities capable of imaging freshly resected tumor specimens could provide frontline non-destructive examination of tissue margins that can be co-integrated with post-operative gold-standard analysis workflows. This has the potential to significantly reduce repeat surgeries, improving patient prognosis and generating substantial savings in the healthcare economy. We introduce a microscopy system utilizing pulsed UV excitation in combination with simultaneously acquired confocal UV reflectance and broadband autofluorescence contrast to rapidly generate deep learning-enabled virtual H&E histology. The imaging speed and realistic virtual histology output that this method promises should find itself well suited to intraoperative analysis of freshly resected tissues.