PROJECT TITLE :

Artificial Intelligence for Colonoscopy Past, Present, and Future

ABSTRACT:

Colonoscopy has seen a significant increase in the number of automated image analysis methods developed over the past few decades. Clinical trials, including several recent studies involving multiple centers, have been used to test the real-time implementation of the most promising methods while performing a colonoscopy. Each trial produced findings that suggested a possible role for the intervention in the prevention of colorectal cancer. In this article, we discuss the history and current state of the development of methods for colonoscopy video analysis, concentrating on two categories of artificial intelligence (AI) technologies that are utilized in clinical trials. These include analysis and feedback for the purpose of enhancing the quality of the colonoscopy, as well as the detection of abnormalities. Methods that employ conventional machine learning algorithms applied to features that have been meticulously designed and hand-crafted have been included in our survey, in addition to more recent methods that employ deep learning. In the final part of this article, we discuss the gap that exists between the current state-of-the-art technology and the desirable clinical features, and we wrap up by discussing the potential future directions of endoscopic artificial intelligence technology development that will help bridge the gap.