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The top 10 results have been unveiled in the first-of-its-kind COVID-19 Lung CT Lesion Segmentation Grand Challenge, a groundbreaking research competition focused on developing artificial intelligence (AI) models to help in the visualization and measurement of COVID specific lesions in the lungs of infected patients, potentially facilitating to more timely and patient-specific medical interventions.
Attracting more than 1,000 global participants, the competition was presented by the Sheikh Zayed Institute for Pediatric Surgical Innovation at Children s National Hospital in collaboration with leading AI technology company NVIDIA and the National Institutes of Health (NIH). The competition s AI models utilized a multi-institutional, multi-national data set provided by public datasets from The Cancer Imaging Archive (National Cancer Institute), NIH and the University of Arkansas, that originated from patients of different ages, genders and with variable disease sever ....

United States , Vitali Liauchuk , Ziqi Zhou , Claire Tang , Mona Flores , Fabian Isensee , Bradford Wood , Qinji Yu , Jan Hendrik Moltz , Marius George Linguraru , Andreas Husch , Diana Troese , Bruno Oliveira , Children National , Cancer Imaging Archive National Institute , Lynbrook High School , German Cancer Research Center , Nagoya University , Shenzhen University , United Institute Of Informatics Problems , Northwestern Polytechnical University , National Institutes Of Health , Polytechnic Institute , Fraunhofer Institute For Digital Medicine , University Of Luxembourg , Shanghai Jiao Tong University ,