“…This was implemented in 20 studies through a range of techniques, including flipping, rotating and geometric transformations, with some benefits for model performances 38,68. Image normalisation, a process whereby image pixel values are standardised to a common scale to ensure model training efficiency, was described in 17 studies, using a variety of methods including contrast adjustment, colour adjustment and normalisation techniques to overcome inconsistencies in the staining process 4,17,23,29,38,42,45,48,59,63,64,68,72,[76][77][78][79][80]. Four studies used predeveloped, open-source image pre-processing pipelines, two of which T A B L E 1 (Continued) Whole Slide Image (WSI) Pre-processing pipeline from https://github.com/deroneriksson/python-wsi-preprocessing, which performs a range of manoeuvres including colour correction, image tiling and tissue identification 38,64,68,78.…”