Published August 15, 2021 | Version PrePrint_V0.1
Conference paper Open

Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images

Description

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.

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Related works

Cites
Dataset: 10.21227/9fsv-tm25 (DOI)

Funding

DeepHealth – Deep-Learning and HPC to Boost Biomedical Applications for Health 825111
European Commission