Deep Unsupervised Learning for Biomedical Image Translation from Harmonic Generation Microscopy Image to H&E-stained Image

This work proposes an unsupervised deep learning-based image translation from Harmonic generation microscopy (HGM) to widely used H&E-stained images. The proposed methodology is promising and hopefully will facilitate adopting HGM in clinical workflows.