Deep learning has been adopted as an effective technique to aid COVID-19 detection and segmentation from computed tomography (CT) images… The major challenge lies in the inadequate public public COVI-19 datasets . The results reveal the benefits of transferring knowledge from non-COVID19 lung lesions, and learning from multiple lung lesion datasets can extract more general features, leading to accurate and robust pre-trained models . We further show the capability of the encoder to learn feature representations of lung lesions which improves segmentation accuracy and facilitates training convergence . These findings promote new insights into transfer learning for CT image segmentation, which can also be further generalized to other medical tasks, which is also possible to be further generalized to other medical tasks. These findings promote new insights into transfer learning to other medical targets, say the authors . Back Back to Mail Online home . Back to the page you came from the page go to view your own version of this article by email us. Back to view our version of the article by commenting on our version on this version of The Daily Mail Online/knewtomography

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Keywords : learning - lung - covid - segmentation - version -

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