Colorectal Polyp Classification Based On Latent Sharing Features Domain from Multiple Endoscopy Images.

Abstract As a method to judge the benign or malignant polyp from endoscope images, some methods have been proposed using an ultra-high magnification endoscope. The ultra-high magnification endoscope enables the diagnosis at the cell level. However, it tends to spend many times for diagnosis and requires specific expensive devices. There are three types of images that are taken for diagnosis by the regular endoscope: white light, dye, and narrowband image (NBI) in general. This paper proposes a benign/malignant polyp classification method using these images taken by the regular endoscope. Each image features derived from endoscope images are extracted by adapting a pre-trained CNN to each domain. Finally, polyps are classified using extracted features. Experiments confirmed that the proposed method enabled the classification of benign or malignant colorectal polyps with over 90% accuracy.