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FTUNet:A Semantic Segmentation Model for Medical Image Lesion Region Based on U-shaped Network and Transformer

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FTUNet

FTUNet: A Semantic Segmentation Model for Medical Image Lesion Region Based on U-shaped Network and Transformer

Paper

https://link.springer.com/article/10.1007/s11063-024-11533-z

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Semantic segmentation is used in a large number of fields, especially in medical image processing. On the other hand, the Transformer has been introduced into the field of Computer Vision. A large number of experiments show that the combination of U-type codec and Transformer can better handle this problem. Specifically, this paper proposes a deep network FTUNet. The model code has been uploaded, and researchers and scholars are welcome to consult.

Environment

he program runs on a high-performance server, with Pytorch version no less than 1.13.0 and Python version 3.8.15.

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FTUNet:A Semantic Segmentation Model for Medical Image Lesion Region Based on U-shaped Network and Transformer

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