Review of computational methods for the detection and classification of polyps in colonoscopy imaging

Abstract

Computer-aided diagnosis (CAD) is a tool with great potential to help endoscopists in the tasks of detecting and histologically classifying colorectal polyps. In recent years, different technologies have been described and their potential utility has been increasingly evidenced, which has generated great expectations among scientific societies. However, most of these works are retrospective and use images of different quality and characteristics which are analysed off line. This review aims to familiarise gastroenterologists with computational methods and the particularities of endoscopic imaging, which have an impact on image processing analysis. Finally, the publicly available image databases, needed to compare and confirm the results obtained with different methods, are presented.

Keywords: Artificial intelligence; Colon polyp; Colonoscopia; Colonoscopy; Computer-aided diagnosis; Detección de pólipos; Diagnóstico asistido por computador; Histological prediction; Inteligencia artificial; Machine learning; Polyp detection; Predicción histológica; Pólipo de colon.