Researchers have made advancements in virtual histology using deep learning and various microscopy techniques, including photoacoustic remote sensing and optical coherence tomography. These methods enable the virtual staining and analysis of biological samples without the need for labels or traditional staining processes. The techniques appear to be applicable to a range of sample types, including human specimens and unprocessed tissues.