A fusion‐attention swin transformer for cardiac MRI image segmentation

A fusion‐attention swin transformer for cardiac MRI image segmentation

Abstract For semantic segmentation of cardiac magnetic resonance image (MRI) with low recognition and high background noise, a fusion‐attention Swin Transformer is proposed based on cognitive science and deep learning methods. It has a U‐shaped symmetric encoding–decoding structure with an attention...

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Bibliographic Details
Main Authors: Ruiping Yang, Kun Liu, Yongquan Liang
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:IET Image Processing
Subjects:
biomedical magnetic resonance imaging
image segmentation
medical image processing
Online Access:https://doi.org/10.1049/ipr2.12936

Internet

https://doi.org/10.1049/ipr2.12936

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