An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vision methods applied to endoscopy and promoti...

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Detalles Bibliográficos
Autores principales: Ali, Sharib, Zhou, Felix, Braden, Barbara, Bailey, Adam, Yang, Suhui, Cheng, Guanju, Zhang, Pengyi, Li, Xiaoqiong, Kayser, Maxime, Soberanis-Mukul, Roger D., Albarqouni, Shadi, Wang, Xiaokang, Wang, Chunqing, Watanabe, Seiryo, Oksuz, Ilkay, Ning, Qingtian, Yang, Shufan, Khan, Mohammad Azam, Gao, Xiaohong W., Realdon, Stefano, Loshchenov, Maxim, Schnabel, Julia A., East, James E., Wagnieres, Georges, Loschenov, Victor B., Grisan, Enrico, Daul, Christian, Blondel, Walter, Rittscher, Jens
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026422/
https://www.ncbi.nlm.nih.gov/pubmed/32066744
http://dx.doi.org/10.1038/s41598-020-59413-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026422/
https://www.ncbi.nlm.nih.gov/pubmed/32066744
http://dx.doi.org/10.1038/s41598-020-59413-5

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