Hyperplastic and Adenoma polyp classification using Deep networks

Colorectal cancer (CRC) is the world’s third most frequent disease. Polyps which are growths that emerge as lumps on the colon lining are often benign, some may develop into malignant tumours over time, thus it is advisable to have them removed to prevent the risk of colorectal cancer. Early identification and characterization of the kind of polyp are crucial for cancer prevention and treatment. DCNNs have proved to be extremely effective in object categorization over a wide range of object categories. In this study, we experimentally evaluated and compared the effectiveness of the ResNet50 and EfficientNetB0 models in distinguishing Hyperplastic from Adenoma polyps and diagnosing them. Our findings show that cutting-edge DCNN models may correctly characterize the polyps with accuracy equivalent to or greater than that predicted by doctors. As a result, our findings might be valuable for future polyp categorization studies.