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Rhode Island gastroenterology video capsule endoscopy data set.
Charoen, Amber; Guo, Averill; Fangsaard, Panisara; Taweechainaruemitr, Supakorn; Wiwatwattana, Nuwee; Charoenpong, Theekapun; Rich, Harlan G.
Afiliación
  • Charoen A; The Warren Alpert Medical School of Brown University, Division of Gastroenterology, Providence, Rhode Island, 02903, United States of America. amber.charoen@brown.edu.
  • Guo A; The Warren Alpert Medical School of Brown University, Division of Gastroenterology, Providence, Rhode Island, 02903, United States of America.
  • Fangsaard P; Chulabhorn Hospital, Chulabhorn Royal Academy, Bangkok, 10210, Thailand.
  • Taweechainaruemitr S; Srinakharinwirot University, Department of Computer Science, Faculty of Science, Bangkok, 10110, Thailand.
  • Wiwatwattana N; Srinakharinwirot University, Department of Computer Science, Faculty of Science, Bangkok, 10110, Thailand.
  • Charoenpong T; Srinakharinwirot University, Department of Biomedical Engineering, Faculty of Engineering, Nakhonnayok, 26120, Thailand.
  • Rich HG; The Warren Alpert Medical School of Brown University, Division of Gastroenterology, Providence, Rhode Island, 02903, United States of America.
Sci Data ; 9(1): 602, 2022 10 06.
Article en En | MEDLINE | ID: mdl-36202840
Complete endoscopic evaluation of the small bowel is challenging due to its length and anatomy. Although several advances have been made to achieve diagnostic and therapeutic goals, including double-balloon enteroscopy, single-balloon enteroscopy, and spiral enteroscopy, video capsule endoscopy (VCE) remains the least invasive tool for complete visualization of the small bowel and is the preferred method for initial diagnostic evaluation. At present, interpretation of VCE data requires manual annotation of landmarks and abnormalities in recorded videos, which can be time consuming. Computer-assisted diagnostic systems using artificial intelligence may help to optimize VCE reading efficiency by reducing the need for manual annotation. Here we present a large VCE data set compiled from studies performed at two United States hospitals in Providence, Rhode Island, including 424 VCE studies and 5,247,588 total labeled images. In conjunction with existing published data sets, these files may aid in the development of algorithms to further improve VCE.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Endoscopía Capsular / Gastroenterología Tipo de estudio: Guideline Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Endoscopía Capsular / Gastroenterología Tipo de estudio: Guideline Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Sci Data Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido