Public Imaging Datasets of Gastrointestinal Endoscopy for Artificial Intelligence: a Review.
J Digit Imaging
; 36(6): 2578-2601, 2023 12.
Article
em En
| MEDLINE
| ID: mdl-37735308
ABSTRACT
With the advances in endoscopic technologies and artificial intelligence, a large number of endoscopic imaging datasets have been made public to researchers around the world. This study aims to review and introduce these datasets. An extensive literature search was conducted to identify appropriate datasets in PubMed, and other targeted searches were conducted in GitHub, Kaggle, and Simula to identify datasets directly. We provided a brief introduction to each dataset and evaluated the characteristics of the datasets included. Moreover, two national datasets in progress were discussed. A total of 40 datasets of endoscopic images were included, of which 34 were accessible for use. Basic and detailed information on each dataset was reported. Of all the datasets, 16 focus on polyps, and 6 focus on small bowel lesions. Most datasets (n = 16) were constructed by colonoscopy only, followed by normal gastrointestinal endoscopy and capsule endoscopy (n = 9). This review may facilitate the usage of public dataset resources in endoscopic research.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Endoscopia por Cápsula
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
J Digit Imaging
Assunto da revista:
DIAGNOSTICO POR IMAGEM
/
INFORMATICA MEDICA
/
RADIOLOGIA
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
China