FFUNet: A novel feature fusion makes strong decoder for medical image segmentation

FFUNet: A novel feature fusion makes strong decoder for medical image segmentation

Abstract Convolutional neural networks (CNNs) have strong ability to extract local features, but it is slightly lacking in extracting global contexts. In contrast, transformers are good at long‐distance modelling due to the global self‐attention mechanisms while its performance in localization is li...

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Bibliographic Details
Main Authors: Junsong Xie, Renju Zhu, Zezhi Wu, Jinling Ouyang
Format: Article
Language:English
Published: Hindawi-IET 2022-07-01
Series:IET Signal Processing
Subjects:
attention mechanism
conformer
deformable convolution
feature fusion
medical image segmentation
skip connection
Online Access:https://doi.org/10.1049/sil2.12114

Internet

https://doi.org/10.1049/sil2.12114

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