CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation

Automatic and precise medical image segmentation (MIS) is of vital importance for clinical diagnosis and analysis. Current MIS methods mainly rely on the convolutional neural network (CNN) or self-attention mechanism (Transformer) for feature modeling. However, CNN-based methods suffer from the inac...

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Veröffentlicht in:	IEEE transactions on circuits and systems for video technology 2024-12, p.1-1
Hauptverfasser:	Wu, Lanhu, Zhang, Miao, Piao, Yongri, Yao, Zhenyan, Sun, Weibing, Tian, Feng, Lu, Huchuan
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy CNN collaborative learning Convolutional neural networks Decoding Feature extraction Federated learning Image segmentation Knowledge transfer Location awareness Medical image segmentation Semantics Transformer Transformers
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