A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging

Jha, D., Ali, S. orcid.org/0000-0003-1313-3542, Hicks, S. et al. (24 more authors) (2021) A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging. Medical Image Analysis, 70. 102007. ISSN 1361-8415

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Jha, D.
  • Ali, S. ORCID logo https://orcid.org/0000-0003-1313-3542
  • Hicks, S.
  • Thambawita, V.
  • Borgli, H.
  • Smedsrud, P.H.
  • de Lange, T.
  • Pogorelov, K.
  • Wang, X.
  • Harzig, P.
  • Tran, M.-T.
  • Meng, W.
  • Hoang, T.-H.
  • Dias, D.
  • Ko, T.H.
  • Agrawal, T.
  • Ostroukhova, O.
  • Khan, Z.
  • Atif Tahir, M.
  • Liu, Y.
  • Chang, Y.
  • Kirkerød, M.
  • Johansen, D.
  • Lux, M.
  • Johansen, H.D.
  • Riegler, M.A.
  • Halvorsen, P.
Copyright, Publisher and Additional Information:

© 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: Gastrointestinal endoscopy challenges, Artificial intelligence, Computer-aided detection and diagnosis, Medical imaging, Medico Task 2017, Medico Task 2018, BioMedia 2019 grand challenge
Dates:
  • Published: May 2021
  • Published (online): 19 February 2021
  • Accepted: 16 February 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence
Depositing User: Symplectic Publications
Date Deposited: 24 Oct 2024 09:37
Last Modified: 24 Oct 2024 09:37
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.media.2021.102007
Related URLs:
Open Archives Initiative ID (OAI ID):

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