Protocol for detecting oral squamous cell carcinoma in histopathology images using the momentum contrast framework

The detection of oral squamous cell carcinoma (OSCC) in histopathology images is crucial for improving diagnostic accuracy and patient outcomes. Here, we present a protocol for detecting OSCC in histopathology images using transfer learning. We describe steps for installing software and prerequisites, preparing datasets, and pretraining a model on images from various tissue types using the momentum contrast (MoCo) framework. We then detail procedures for evaluating the fine-tuned HistoMOCO model's performance on a test dataset.