Deep learning-enabled fluorescence imaging for surgical guidance: training for oral cancer depth quantification.

Significance: Oral cancer surgery requires accurate margin delineation to balance complete resection with post-operative functionality. Current fluorescence imaging systems provide two-dimensional margin assessment yet fail to quantify tumor depth prior to resection. Harnessing structured light in combination with deep learning (DL) may provide near real-time three-dimensional margin detection.

Correction: Won et al. Ex Vivo Perfusion Using a Mathematical Modeled, Controlled Gas Exchange Self-Contained Bioreactor Can Maintain a Mouse Kidney for Seven Days. 2022, , 1822.

In the original publication [...

Ex Vivo Perfusion Using a Mathematical Modeled, Controlled Gas Exchange Self-Contained Bioreactor Can Maintain a Mouse Kidney for Seven Days.

Regenerative medicine requires better pre-clinical tools in order to increase the efficiency of novel therapies transitioning to the clinic. Current monolayer cell culture methods are suboptimal for effectively testing new therapies and live mouse models are expensive, time consuming and require invasive procedures. Fetal organ culture, organoids, microfluidics and culture of thick sections of adult organs all aim to fill the knowledge gap between monolayer culture and live mouse studies.