Polyp Classification and Clustering from Endoscopic Images using Competitive and Convolutional Neural Networks

Understanding the type of Polyp present in the body plays an important role in medical diagnosis. This paper proposes an approach to classify and cluster the polyp present in an Endoscopic scene into malignant or benign class. CNN and Self Organizing Maps are used to classify and cluster from white light and Narrow Band (NBI) Endoscopic Images . Using Competitive Neural Network different polyps available from previous data are plotted with the new polyp according to their structural similarity. Such kind of presentation not only help the doctor in it’s easy understanding but also helps him to know what kind of medical procedures were followed in similar cases.

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