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Computational pathology has been transforming the traditional practice of pathology through the integration of AI and WSI analysis techniques. Specifically regarding the assessment of different tissue dyes, virtual staining is a promising approach to simulate histological staining on WSI. It leverages advanced image processing and machine learning models to digitally replicate conventional histological stains, such as IHC.

By virtually mimicking the staining process, this technique generates multiple digital slides from a single H&E sample, promoting the efficient use of resources, preservation of tissue specimens, as well as reduction of lab workload and costs. Additionally, virtual staining reduces the turnaround time for diagnoses, enabling faster and more accurate assessments of patient cases. Moreover, virtual staining allows for the customisation of staining patterns, tailoring the visualisation to emphasise specific tissue features and potentially uncovering hidden details that might be otherwise challenging to visualise with conventional staining. Therefore, this approach represents a promising approach that has the potential to revolutionise how pathologists analyse tissue samples. It is expected to play an increasingly significant role in research, diagnostics, and personalised medicine, ultimately enhancing patient care and improving healthcare outcomes.