AUTHOR=Paderno Alberto , Gennarini Francesca , Sordi Alessandra , Montenegro Claudia , Lancini Davide , Villani Francesca Pia , Moccia Sara , Piazza Cesare TITLE=Artificial intelligence in clinical endoscopy: Insights in the field of videomics JOURNAL=Frontiers in Surgery VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/surgery/articles/10.3389/fsurg.2022.933297 DOI=10.3389/fsurg.2022.933297 ISSN=2296-875X ABSTRACT=

Artificial intelligence is being increasingly seen as a useful tool in medicine. Specifically, these technologies have the objective to extract insights from complex datasets that cannot easily be analyzed by conventional statistical methods. While promising results have been obtained for various -omics datasets, radiological images, and histopathologic slides, analysis of videoendoscopic frames still represents a major challenge. In this context, videomics represents a burgeoning field wherein several methods of computer vision are systematically used to organize unstructured data from frames obtained during diagnostic videoendoscopy. Recent studies have focused on five broad tasks with increasing complexity: quality assessment of endoscopic images, classification of pathologic and nonpathologic frames, detection of lesions inside frames, segmentation of pathologic lesions, and in-depth characterization of neoplastic lesions. Herein, we present a broad overview of the field, with a focus on conceptual key points and future perspectives.