Reference : Rapid Artificial Intelligence Solutions in a Pandemic - The COVID-19-20 Lung CT Lesio...
E-prints/Working papers : Already available on another site
Life sciences : Multidisciplinary, general & others
Systems Biomedicine
http://hdl.handle.net/10993/47586
Rapid Artificial Intelligence Solutions in a Pandemic - The COVID-19-20 Lung CT Lesion Segmentation Challenge.
English
Roth, Holger [> >]
Xu, Ziyue [> >]
Diez, Carlos Tor [> >]
Jacob, Ramon Sanchez [> >]
Zember, Jonathan [> >]
Molto, Jose [> >]
Li, Wenqi [> >]
Xu, Sheng [> >]
Turkbey, Baris [> >]
Turkbey, Evrim [> >]
Yang, Dong [> >]
Harouni, Ahmed [> >]
Rieke, Nicola [> >]
Hu, Shishuai [> >]
Isensee, Fabian [> >]
Tang, Claire [> >]
Yu, Qinji [> >]
Sölter, Jan [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Interventional Neuroscience]
Zheng, Tong [> >]
Liauchuk, Vitali [> >]
Zhou, Ziqi [> >]
Moltz, Jan [> >]
Oliveira, Bruno [> >]
Xia, Yong [> >]
Maier-Hein, Klaus [> >]
Li, Qikai [> >]
Husch, Andreas mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Interventional Neuroscience]
Zhang, Luyang [> >]
Kovalev, Vassili [> >]
Kang, Li [> >]
Hering, Alessa [> >]
Vilaça, João [> >]
Flores, Mona [> >]
Xu, Daguang [> >]
Wood, Bradford [> >]
Linguraru, Marius [> >]
2021
No
[en] Artificial intelligence (AI) methods for the automatic detection and quantification of COVID-19 lesions in chest computed tomography (CT) might play an important role in the monitoring and management of the disease. We organized an international challenge and competition for the development and comparison of AI algorithms for this task, which we supported with public data and state-of-the-art benchmark methods. Board Certified Radiologists annotated 295 public images from two sources (A and B) for algorithms training (n=199, source A), validation (n=50, source A) and testing (n=23, source A; n=23, source B). There were 1,096 registered teams of which 225 and 98 completed the validation and testing phases, respectively. The challenge showed that AI models could be rapidly designed by diverse teams with the potential to measure disease or facilitate timely and patient-specific interventions. This paper provides an overview and the major outcomes of the COVID-19 Lung CT Lesion Segmentation Challenge - 2020.
Researchers ; Professionals
http://hdl.handle.net/10993/47586
https://www.researchsquare.com/article/rs-571332/v1
FnR ; FNR14702831 > Andreas Husch > AICovIX > Ai Based Diagnosis Of Covid-19 From Ct/X-ray Imaging > 01/06/2020 > 30/11/2020 > 2020

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