Deep Learning-Driven Models for Endoscopic Image Analysis

The advent of video endoscopy has led to an increased interest in the development of computer-aided diagnosis (CAD) approaches. Many of these focus on the use of deep learning methods as a means of automatically identifying abnormalities during endoscopy to lessen the workload on doctors. In this chapter, we take two tasks in endoscopic image analysis as examples, to survey the state of the art, recent advances, and future directions of CAD applications, especially with regard to deep learning models. We introduce the fundamentals of deep learning-driven methods and elaborate on their success in areas such as endoscopic image classification, detection of abnormal regions, and lesion boundary segmentation.