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17th European Conference on Computer Vision, ECCV 2022 ; 13807 LNCS:500-516, 2023.
Article in English | Scopus | ID: covidwho-2266327

ABSTRACT

Since COVID strongly affects the respiratory system, lung CT-scans can be used for the analysis of a patients health. We introduce a neural network for the prediction of the severity of lung damage and the detection of a COVID-infection using three-dimensional CT-data. Therefore, we adapt the recent ConvNeXt model to process three-dimensional data. Furthermore, we design and analyze different pretraining methods specifically designed to improve the models ability to handle three-dimensional CT-data. We rank 2nd in the 1st COVID19 Severity Detection Challenge and 3rd in the 2nd COVID19 Detection Challenge. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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