Transfer Learning-Based Classification of Gastrointestinal Polyps

We used a deep learning model, called Inception V3, to classify colorectal polyps into: hyperplastic, serrated and adenoma lesions using colonoscopy images. Inception V3 is a convolution neural network (CNN) pre-trained on an extremely large dataset, which is based on multi-branch convolutional networks. Because we have a relative small dataset, we use transfer learning (TL) to transfer the optimal weights of hundreds of hours of training across multiple high-power GPUs. A dataset 152 instances containing 76 polyps belonging to the three lesion types was used. We re-trained the last five layers of Inception V3 with two-thirds of the images in the dataset. The results obtained with our new neural network model are satisfactory compared to other works and human experts.

Automated summary

The study utilized the Inception V3 deep learning model to classify colorectal polyps and transfer the training weights through transfer learning, achieving satisfactory results compared to other works and human experts.