A comprehensive analysis of classification methods in gastrointestinal endoscopy imaging

•Benchmark of computer vision methods for multi-class gastroendoscopy image classification.•Longitudinal analysis for three consecutive years (2017 till 2019) crowd-source Medico challenge initiative.•Comprehensive analysis of methods on same dataset reveal the continuous progress of method developm...

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Veröffentlicht in:	Medical image analysis 2021-05, Vol.70, p.102007-102007, Article 102007
Hauptverfasser:	Jha, Debesh, Ali, Sharib, Hicks, Steven, Thambawita, Vajira, Borgli, Hanna, Smedsrud, Pia H., de Lange, Thomas, Pogorelov, Konstantin, Wang, Xiaowei, Harzig, Philipp, Tran, Minh-Triet, Meng, Wenhua, Hoang, Trung-Hieu, Dias, Danielle, Ko, Tobey H., Agrawal, Taruna, Ostroukhova, Olga, Khan, Zeshan, Atif Tahir, Muhammad, Liu, Yang, Chang, Yuan, Kirkerød, Mathias, Johansen, Dag, Lux, Mathias, Johansen, Håvard D., Riegler, Michael A., Halvorsen, Pål
Format:	Artikel
Sprache:	eng
Schlagworte:	Abnormalities Artificial intelligence BioMedia 2019 grand challenge Cancer Classification Computer applications Computer vision Computer-aided detection and diagnosis Correlation coefficient Correlation coefficients Endoscopy Gastrointestinal endoscopy challenges Informasjons- og kommunikasjonsvitenskap: 420 Information and communication science: 420 Matematikk og Naturvitenskap: 400 Mathematics and natural science: 400 Medical imaging Medico Task 2017 Medico Task 2018 Multimedia Surveillance VDP
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