CA-SegNet: A channel-attention encoder-decoder network for histopathological image segmentation - Groupe INSA
Article Dans Une Revue Biomedical Signal Processing and Control Année : 2024

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

Résumé

A novel deep learning-based CA-SegNet model for histopathological image segmentation.

• A channel-attention feature fusion module (CAFFM) that significantly improves shallow feature reuse.

• A bottleneck-structured decoder developed for better feature integration.

• Outstanding segmentation performance on both large and small-scale datasets.

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Dates et versions

hal-04852251 , version 1 (20-12-2024)

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Citer

Feng He, Weibo Wang, Lijuan Ren, Yixuan Zhao, Zhengjun Liu, et al.. CA-SegNet: A channel-attention encoder-decoder network for histopathological image segmentation. Biomedical Signal Processing and Control, 2024, 96, pp.106590. ⟨10.1016/j.bspc.2024.106590⟩. ⟨hal-04852251⟩
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