Cargando…
Automatic detection of multiple types of pneumonia: Open dataset and a multi-scale attention network
The quick and precise identification of COVID-19 pneumonia, non-COVID-19 viral pneumonia, bacterial pneumonia, mycoplasma pneumonia, and normal lung on chest CT images play a crucial role in timely quarantine and medical treatment. However, manual identification is subject to potential misinterpreta...
Autores principales: | Wong, Pak Kin, Yan, Tao, Wang, Huaqiao, Chan, In Neng, Wang, Jiangtao, Li, Yang, Ren, Hao, Wong, Chi Hong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8660060/ https://www.ncbi.nlm.nih.gov/pubmed/34909050 http://dx.doi.org/10.1016/j.bspc.2021.103415 |
Ejemplares similares
-
Automatic distinction between COVID-19 and common pneumonia using multi-scale convolutional neural network on chest CT scans
por: Yan, Tao, et al.
Publicado: (2020) -
Automatic lumbar spinal MRI image segmentation with a multi-scale attention network
por: Li, Haixing, et al.
Publicado: (2021) -
Multi-scale U-like network with attention mechanism for automatic pancreas segmentation
por: Yan, Yingjing, et al.
Publicado: (2021) -
MCA-UNet: multi-scale cross co-attentional U-Net for automatic medical image segmentation
por: Wang, Haonan, et al.
Publicado: (2023) -
Multi-scale ResNet and BiGRU automatic sleep staging based on attention mechanism
por: Liu, Changyuan, et al.
Publicado: (2022)