CA-SegNet: A channel-attention encoder–decoder network for histopathological image segmentation

Histopathological image segmentation based on encoder–decoder architectures has emerged as a pivotal research area in medical image analysis. However, due to the irrelevant information within multi-channel representations from the encoder, the coarse reuse of shallow features in skip connections may...

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Veröffentlicht in:	Biomedical signal processing and control Jg. 96; S. 106590
Hauptverfasser:	He, Feng, Wang, Weibo, Ren, Lijuan, Zhao, Yixuan, Liu, Zhengjun, Zhu, Yuemin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.10.2024 Elsevier
Schlagworte:	Channel attention Computer Science Deep learning Encoder–decoder Histopathological images Medical image segmentation Medical Imaging Deep learning Encoder–decoder Channel attention Histopathological images Medical image segmentation Deep learning Channel attention Encoder-decoder Medical image segmentation Histopathological images
ISSN:	1746-8094
Online-Zugang:	Volltext
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