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3D U-Net For Segmentation of Covid-19-Associated Pulmonary Infiltrates Using Transfer Learning: State-Of-The-Art Results on Affordable Hardware

2021-03-11

Abstract excerpt

<title>Abstract</title> <p>Segmentation of pulmonary infiltrates can help assess severity of COVID-19, but manual segmentation is labor and time-intensive. Using neural networks to segment pulmonary infiltrates would enable automation of this task. However, training a 3D U-Net from computed tomography (CT) data is time- and resource-intensive. In this work, we therefore developed and tested a solution on how tran...

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Literature Corpus work: 2cc5824f-37ef-5c89-82fc-c496e71290f7
DOI: 10.21203/rs.3.rs-259319/v1

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