  Colorectal cancer is a leading cause of cancer death for both men and women.
For this reason, histopathological characterization of colorectal polyps is the
major instrument for the pathologist in order to infer the actual risk for
cancer and to guide further follow-up. Colorectal polyps diagnosis includes the
evaluation of the polyp type, and more importantly, the grade of dysplasia.
This latter evaluation represents a critical step for the clinical follow-up.
The proposed deep learning-based classification pipeline is based on
state-of-the-art convolutional neural network, trained using proper
countermeasures to tackle WSI high resolution and very imbalanced dataset. The
experimental results show that one can successfully classify adenomas dysplasia
grade with 70% accuracy, which is in line with the pathologists' concordance.
