Titlebook: Atlas of Advanced Endoscopy; Yasushi Sano,Philip Chiu,Chikatoshi Katada Book 2024 The Editor(s) (if applicable) and The Author(s), under e

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David W. Embley,Bernhard Thalheim(M-NBI) of the stomach [2]. The VS classification system employs anatomical terms as endoscopic markers for analysis. Anatomical components visualized using M-NBI were divided into microvascular (MV) and microsurface (MS) patterns. As shown in ◘ Fig. 1a–c, the subepithelial capillary and collecting

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Meike Klettke,Bernhard Thalheimcation [1]. NBI observation became widely recognized as an essential method for colorectal tumor diagnosis. In 2009, an international collaborative research group called the Colon Tumor NBI Interest Group (CTNIG), led by experts from Japan (Yasushi Sano, Shinji Tanaka), France (Ponchon T), the Unite

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EVIS X1 Endoscopy Systemcal signals and displaying them on a monitor was developed in Japan in 1986 [1]. Subsequently, models such as CV-240 (1997), CV-260, Lucera Spectrum (2006), and CV-290, Lucera Elite (2010) have evolved remarkably in terms of image quality and functionality. Notably, the recent introduction of the CV

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Artificial Intelligence (AI) in Colonoscopynt focus has been the integration of AI in medical imaging. In particular, systems referred to as computer-aided detection and diagnosis (CADe and CADx) have demonstrated considerable promise in the realm of gastrointestinal endoscopy. These systems employ AI to aid endoscopists in identifying abnor

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