Ultraviolet photoacoustic remote sensing and scattering microscopy for CycleGAN-enabled realistic virtual histology

Abstract

Ultraviolet photoacoustic remote sensing microscopy provides label-free optical absorption contrast comparable to hematoxylin staining. This has been combined with 266 nm optical scattering microscopy offering eosin-like contrast. Here, we use unsupervised deep learning-based style transfer using the CycleGAN approach to render these pseudo-colored virtual histological images in a realistic stain style comparable to the H&E gold standard in unstained human and murine tissue specimens. A multi-pathologist diagnostic concordance study found a sensitivity of 89%, specificity of 91%, and accuracy of 90%. A blinded subjective stain quality survey suggested virtual histology was preferred over frozen sections at the 95% confidence level.