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

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 fr...

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Detalles Bibliográficos
Autores principales:	Siripoppohn, Vitchaya, Pittayanon, Rapat, Tiankanon, Kasenee, Faknak, Natee, Sanpavat, Anapat, Klaikaew, Naruemon, Vateekul, Peerapon, Rerknimitr, Rungsun
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Korean Society of Gastrointestinal Endoscopy 2022
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178134/ https://www.ncbi.nlm.nih.gov/pubmed/35534933 http://dx.doi.org/10.5946/ce.2022.005

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