Real-time semantic segmentation of gastric intestinal metaplasia using a deep learning approach

• Hauptverfasser: Vitchaya Siripoppohn (Verfasst von), Rapat Pittayanon (Verfasst von), Kasenee Tiankanon (Verfasst von), Natee Faknak (Verfasst von), Anapat Sanpavat (Verfasst von), Naruemon Klaikaew (Verfasst von), Peerapon Vateekul (Verfasst von), Rungsun Rerknimitr (Verfasst von)
• Format: Buch
• Veröffentlicht: Korean Society of Gastrointestinal Endoscopy, 2022-05-01T00:00:00Z.
• Schlagworte: article
• Online-Zugang: Connect to this object online.

Background/Aims Previous artificial intelligence (AI) models attempting to segment gastric intestinal metaplasia (GIM) areas have failed to be deployed in real-time endoscopy due to their slow inference speeds. Here, we propose a new GIM segmentation AI model with inference speeds faster than 25 fra...