2022
DOI: 10.1002/ima.22819
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COVID‐19 lung infection segmentation from chest CT images based on CAPA‐ResUNet

Abstract: Coronavirus disease 2019 (COVID-19) epidemic has devastating effects on personal health around the world. It is significant to achieve accurate segmentation of pulmonary infection regions, which is an early indicator of disease. To solve this problem, a deep learning model, namely, the content-aware preactivated residual UNet (CAPA-ResUNet), was proposed for segmenting COVID-19 lesions from CT slices. In this network, the pre-activated residual block was used for down-sampling to solve the problems of complex … Show more

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“…For segmenting COVID‐19 lesions from CT slices, Ma et al 50 propose the content‐aware pre‐activated residual UNet, CAPA‐ResUNet. Polat 51 presents a useful segmentation framework based on the modified DeepLabV3+ using lower atrous rates in the atrous spatial pyramid pooling module.…”
Section: Segmentationmentioning
confidence: 99%
“…For segmenting COVID‐19 lesions from CT slices, Ma et al 50 propose the content‐aware pre‐activated residual UNet, CAPA‐ResUNet. Polat 51 presents a useful segmentation framework based on the modified DeepLabV3+ using lower atrous rates in the atrous spatial pyramid pooling module.…”
Section: Segmentationmentioning
confidence: 99%