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

2022-06-30 · Daniel Kienzle, Julian Lorenz, Robin Schön, Katja Ludwig, Rainer Lienhart

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.

📄 PDF Abstract BibTeX arXiv:2206.15073

Code (1)

kiedani/submission_2nd_covid19_competition 공식 구현 pytorch

Tasks

severity prediction

Methods 이 논문이 사용한 방법론

ConvNeXt 설명 없음

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