Comprehensive digital chemical pathology using stimulated Raman scattering

Histopathology, a fundamental biomedical tissue assessment method, is being revolutionized by Stimulated Raman Scattering (SRS) microscopy. This technique, which directly measures tissue molecular composition, eliminates conventional processing and staining. We integrate SRS into pathology workflows, capturing chemical data from minimally processed tissues using optical sectioning for thick tissue imaging. A generative adversarial network (GAN) pipeline creates virtual H&E stained images and mimics formalin-fixed, paraffin-embedded tissue morphology. This rapid, preservative approach maintains diagnostic reliability and enhances capabilities by preserving lipids and small molecules. Additionally, we explore "deepfake pathology" for complement existing datasets and enhance the representation of rare pathology cases.