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arXiv · 2206.15073

COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings

Daniel Kienzle·Julian Lorenz·Robin Schön·Katja Ludwig·Rainer Lienhart
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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.

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Daniel Kienzle, Julian Lorenz, Robin Schön, Katja Ludwig, Rainer Lienhart. 2022-06-30. COVID Detection and Severity Prediction with 3D-ConvNeXt and Custom Pretrainings. https://arxiv.org/abs/2206.15073

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