Paras Lakhani, J Mongan, C Singhal, Q Zhou, K P Andriole, W F Auffermann, P M Prasanna, T X Pham, Michael Peterson, P J Bergquist, T S Cook, S F Ferraciolli, G C A Corradi, M S Takahashi, C S Workman, M Parekh, S I Kamel, J Galant, A Mas-Sanchez, E C Benítez, M Sánchez-Valverde, L Jaques, M Panadero, M Vidal, M Culiañez-Casas, D Angulo-Gonzalez, S G Langer, María de la Iglesia-Vayá, G Shih
We describe the curation, annotation methodology, and characteristics of the dataset used in an artificial intelligence challenge for detection and localization of COVID-19 on chest radiographs. The chest radiographs were annotated by an international group of radiologists into four mutually exclusive categories, including "typical," "indeterminate," and "atypical appearance" for COVID-19, or "negative for pneumonia," adapted from previously published guidelines, and bounding boxes were placed on airspace opacities...
September 28, 2022: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology