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RCTE: A reliable and consistent temporal-ensembling framework for semi-supervised segmentation of COVID-19 lesions.
Ding W, Abdel-Basset M, Hawash H. Ding W, et al. Inf Sci (N Y). 2021 Nov;578:559-573. doi: 10.1016/j.ins.2021.07.059. Epub 2021 Jul 21. Inf Sci (N Y). 2021. PMID: 34305162 Free PMC article.
The segmentation of COVID-19 lesions from computed tomography (CT) scans is crucial to develop an efficient automated diagnosis system. Deep learning (DL) has shown success in different segmentation tasks. ...
The segmentation of COVID-19 lesions from computed tomography (CT) scans is crucial to develop an efficient automated diagnosis syste …
CoV2-Detect-Net: Design of COVID-19 prediction model based on hybrid DE-PSO with SVM using chest X-ray images.
Dixit A, Mani A, Bansal R. Dixit A, et al. Inf Sci (N Y). 2021 Sep;571:676-692. doi: 10.1016/j.ins.2021.03.062. Epub 2021 Apr 6. Inf Sci (N Y). 2021. PMID: 33840820 Free PMC article.
For Covid-19 suspected cases, it is critical to diagnose them accurately and rapidly so that they can be isolated and provided with required medical care. A self-learning automation model will be helpful to diagnose the COVID-19 suspected individual using chest X-rays. ...
For Covid-19 suspected cases, it is critical to diagnose them accurately and rapidly so that they can be isolated and provided with required …