Virtual histology is a non-destructive way to examine tissue in three dimensions before the sample is cut into slides. It usually relies on high-resolution X-ray microtomography or similar volumetric imaging to reveal internal structure while preserving the specimen for later laboratory tests. This is useful when tissue is scarce, when spatial context matters, or when scientists want to keep the same sample available for histological, molecular, or genomic analysis.
In cyber-security terms, virtual histology is a good example of a data pipeline that must be trusted end to end. The scan, metadata, annotations, and AI-assisted analysis all need validation, versioning, and traceability. If acquisition settings, labels, or model outputs are altered or mismanaged, the final interpretation can be wrong even when the image itself looks correct. Defenders care about this because integrity failures in scientific imaging can be just as damaging as tampering with any other high-value digital evidence.